Join Us in Shaping the Future of AI at Barclays. We're launching an exciting new initiative at Barclays to design, build, and scale next-generation platform components that empower developers - including Quants and Strats - to create high-performance, AI-driven applications. As an AI/MLOps Platform Engineer, you'll play a pivotal role in this transformation, working hands-on to develop the infrastructure and tooling that supports the full lifecycle of machine learning and generative AI workloads. This is more than an engineering role-it's an opportunity to influence technical direction, collaborate across diverse teams, and help define how AI and GenAI are delivered at scale. To be successful as an AI/MLOps Platform Engineer at this level, you should have experience with: Proficiency in Python engineering skills, especially in backend systems and infrastructure. Deep AWS expertise, including services like SageMaker, Lambda, ECS, Step Functions, S3, IAM, KMS, CloudFormation, and Bedrock. Proven experience building and scaling MLOps platforms and supporting GenAI workloads in production. Strong understanding of secure software development, cloud cost optimization, and platform observability. Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Demonstrated leadership in setting technical direction while remaining hands-on. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases. Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment. Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role can be based out of our Glasgow or Canary Wharf office. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
Dec 21, 2025
Full time
Join Us in Shaping the Future of AI at Barclays. We're launching an exciting new initiative at Barclays to design, build, and scale next-generation platform components that empower developers - including Quants and Strats - to create high-performance, AI-driven applications. As an AI/MLOps Platform Engineer, you'll play a pivotal role in this transformation, working hands-on to develop the infrastructure and tooling that supports the full lifecycle of machine learning and generative AI workloads. This is more than an engineering role-it's an opportunity to influence technical direction, collaborate across diverse teams, and help define how AI and GenAI are delivered at scale. To be successful as an AI/MLOps Platform Engineer at this level, you should have experience with: Proficiency in Python engineering skills, especially in backend systems and infrastructure. Deep AWS expertise, including services like SageMaker, Lambda, ECS, Step Functions, S3, IAM, KMS, CloudFormation, and Bedrock. Proven experience building and scaling MLOps platforms and supporting GenAI workloads in production. Strong understanding of secure software development, cloud cost optimization, and platform observability. Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Demonstrated leadership in setting technical direction while remaining hands-on. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases. Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment. Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role can be based out of our Glasgow or Canary Wharf office. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
Join Us in Shaping the Future of AI at Barclays. We're launching an exciting new initiative at Barclays to design, build, and scale next-generation platform components that empower developers - including Quants and Strats - to create high-performance, AI-driven applications. As an AI/MLOps Platform Engineer, you'll play a pivotal role in this transformation, working hands-on to develop the infrastructure and tooling that supports the full lifecycle of machine learning and generative AI workloads. This is more than an engineering role-it's an opportunity to influence technical direction, collaborate across diverse teams, and help define how AI and GenAI are delivered at scale. To be successful as an AI/MLOps Platform Engineer at this level, you should have experience with: Proficiency in Python engineering skills, especially in backend systems and infrastructure. Deep AWS expertise, including services like SageMaker, Lambda, ECS, Step Functions, S3, IAM, KMS, CloudFormation, and Bedrock. Proven experience building and scaling MLOps platforms and supporting GenAI workloads in production. Strong understanding of secure software development, cloud cost optimization, and platform observability. Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Demonstrated leadership in setting technical direction while remaining hands-on. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases. Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment. Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role can be based out of our Glasgow or Canary Wharf office. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
Dec 21, 2025
Full time
Join Us in Shaping the Future of AI at Barclays. We're launching an exciting new initiative at Barclays to design, build, and scale next-generation platform components that empower developers - including Quants and Strats - to create high-performance, AI-driven applications. As an AI/MLOps Platform Engineer, you'll play a pivotal role in this transformation, working hands-on to develop the infrastructure and tooling that supports the full lifecycle of machine learning and generative AI workloads. This is more than an engineering role-it's an opportunity to influence technical direction, collaborate across diverse teams, and help define how AI and GenAI are delivered at scale. To be successful as an AI/MLOps Platform Engineer at this level, you should have experience with: Proficiency in Python engineering skills, especially in backend systems and infrastructure. Deep AWS expertise, including services like SageMaker, Lambda, ECS, Step Functions, S3, IAM, KMS, CloudFormation, and Bedrock. Proven experience building and scaling MLOps platforms and supporting GenAI workloads in production. Strong understanding of secure software development, cloud cost optimization, and platform observability. Ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Demonstrated leadership in setting technical direction while remaining hands-on. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases. Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment. Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role can be based out of our Glasgow or Canary Wharf office. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance. Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
Opus Recruitment Solutions
Bristol, Gloucestershire
We are seeking a Fractional CTO to lead the strategic and technical direction of our SaaS client. This role is primarily focused on strategy, architecture, and leadership, while maintaining enough hands-on technical fluency to guide a team of six developers working with a modern AWS-based stack. Rate wise, this is outside IR35 and will involve weekly on-site visits to central Bristol. The Fractional CTO will be responsible for getting the AI Platform live. From there, the focus will be ensuring scalability and security, and aligning technology decisions with business objectives. You will act as the bridge between executive leadership and engineering, ensuring the platform is delivered on time, within budget, and to enterprise-grade standards. Key Responsibilities Define and execute the technology vision and roadmap for the Agentic AI SaaS platform. Provide thought leadership on AI-driven SaaS trends, agentic architectures, and B2B adoption. Lead, mentor, and inspire a team of 6 developers, fostering a culture of collaboration, innovation, and accountability. Guide the design and build of microservices behind API Gateway (REST/HTTP), running on Lambda and/or containerized workloads on EC2/Fargate.
Dec 20, 2025
Contractor
We are seeking a Fractional CTO to lead the strategic and technical direction of our SaaS client. This role is primarily focused on strategy, architecture, and leadership, while maintaining enough hands-on technical fluency to guide a team of six developers working with a modern AWS-based stack. Rate wise, this is outside IR35 and will involve weekly on-site visits to central Bristol. The Fractional CTO will be responsible for getting the AI Platform live. From there, the focus will be ensuring scalability and security, and aligning technology decisions with business objectives. You will act as the bridge between executive leadership and engineering, ensuring the platform is delivered on time, within budget, and to enterprise-grade standards. Key Responsibilities Define and execute the technology vision and roadmap for the Agentic AI SaaS platform. Provide thought leadership on AI-driven SaaS trends, agentic architectures, and B2B adoption. Lead, mentor, and inspire a team of 6 developers, fostering a culture of collaboration, innovation, and accountability. Guide the design and build of microservices behind API Gateway (REST/HTTP), running on Lambda and/or containerized workloads on EC2/Fargate.
Head of AI Salary: 100,000 - 150,000 + bonus Location: London/Hybrid Data Idols are partnering with a major UK brand undergoing a significant enterprise-wide transformation, placing AI at the centre of its long-term business and technology strategy. This is a pivotal, newly created leadership role with the remit to define, influence, and drive the organisation's entire AI agenda. The Opportunity As Head of AI, you will shape the strategic direction for how AI, including generative, agentic, and operational AI, is adopted, governed, and scaled across the organisation. You'll create and lead a high-impact AI function that brings together existing ML, AI Ops, and emerging AI capabilities under a clear, unified strategy. This role is about vision, influence, and enterprise-wide impact. You'll work closely with executive stakeholders to identify where AI can deliver meaningful commercial value, create competitive advantage, and transform customer and operational experiences. You will champion the responsible and strategic adoption of AI, ensuring cutting-edge technologies translate into measurable outcomes. While you'll have a strong technical grounding, this is not a hands-on research or engineering position. Instead, you'll provide strategic leadership, ensuring the right capabilities, standards, and governance structures are in place to successfully deliver AI at scale. Key Responsibilities Set the enterprise AI strategy, aligning AI capabilities with long-term business goals Build, lead, and inspire a new AI organisation, consolidating and uplifting existing teams Drive adoption of generative, agentic, and advanced operational AI across diverse business areas Influence senior stakeholders and guide the organisation on where and how AI can create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder engagement skills, able to operate confidently at senior levels Demonstrated ability to build new teams and uplift organisational capability If you are motivated by shaping the future of AI within a major organisation and leading an agenda with significant executive visibility and impact, please submit your CV for initial screening. Head of AI
Dec 20, 2025
Full time
Head of AI Salary: 100,000 - 150,000 + bonus Location: London/Hybrid Data Idols are partnering with a major UK brand undergoing a significant enterprise-wide transformation, placing AI at the centre of its long-term business and technology strategy. This is a pivotal, newly created leadership role with the remit to define, influence, and drive the organisation's entire AI agenda. The Opportunity As Head of AI, you will shape the strategic direction for how AI, including generative, agentic, and operational AI, is adopted, governed, and scaled across the organisation. You'll create and lead a high-impact AI function that brings together existing ML, AI Ops, and emerging AI capabilities under a clear, unified strategy. This role is about vision, influence, and enterprise-wide impact. You'll work closely with executive stakeholders to identify where AI can deliver meaningful commercial value, create competitive advantage, and transform customer and operational experiences. You will champion the responsible and strategic adoption of AI, ensuring cutting-edge technologies translate into measurable outcomes. While you'll have a strong technical grounding, this is not a hands-on research or engineering position. Instead, you'll provide strategic leadership, ensuring the right capabilities, standards, and governance structures are in place to successfully deliver AI at scale. Key Responsibilities Set the enterprise AI strategy, aligning AI capabilities with long-term business goals Build, lead, and inspire a new AI organisation, consolidating and uplifting existing teams Drive adoption of generative, agentic, and advanced operational AI across diverse business areas Influence senior stakeholders and guide the organisation on where and how AI can create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder engagement skills, able to operate confidently at senior levels Demonstrated ability to build new teams and uplift organisational capability If you are motivated by shaping the future of AI within a major organisation and leading an agenda with significant executive visibility and impact, please submit your CV for initial screening. Head of AI
Lead AI Solutions Architect 6 Month initial contract (Hybrid/London) Up to 750 per day Inside IR35 Government client Overview We are seeking a highly experienced Lead AI Solutions Architect to spearhead the design and implementation of scalable AI solutions and develop Target Operating Models (TOMs) that align with strategic goals. This role is pivotal in accelerating the adoption of transformative AI tools across government departments, ensuring ethical, secure, and impactful delivery. Key Responsibilities Architect enterprise-level AI frameworks and solutions. Design and implement Target Operating Models for AI integration. Ensure compliance with government standards and security protocols. Collaborate with senior stakeholders to align AI strategy with business goals. Contribute to reusable architecture patterns and internal capability uplift. Mentor teams and support cross-government alignment of AI initiatives. Required Experience & Skills Proven experience scaling AI solutions in complex, regulated environments. Deep understanding of the AI/ML lifecycle, model governance, and ethical AI. Hands-on experience with platforms such as AWS Bedrock, Azure AI Foundry, Google Vertex, and open-source AI/ML stacks. Familiarity with Agentic AI Frameworks and risk-based AI assurance. Strong grasp of DPIAs, data protection, and transparency requirements. Excellent communication skills for engaging with senior stakeholders and multidisciplinary teams. Background in regulated environments with the ability to translate complex requirements into deliverable solutions. Additional Criteria Direct authorship of solution design documentation. Experience in developing architectural guardrails and technical standards. Hands-on delivery of AI solutions - not just oversight. Preference for candidates with a "doer" mindset - technically capable and execution-focused. People Source Consulting Ltd is acting as an Employment Business in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas.
Dec 20, 2025
Contractor
Lead AI Solutions Architect 6 Month initial contract (Hybrid/London) Up to 750 per day Inside IR35 Government client Overview We are seeking a highly experienced Lead AI Solutions Architect to spearhead the design and implementation of scalable AI solutions and develop Target Operating Models (TOMs) that align with strategic goals. This role is pivotal in accelerating the adoption of transformative AI tools across government departments, ensuring ethical, secure, and impactful delivery. Key Responsibilities Architect enterprise-level AI frameworks and solutions. Design and implement Target Operating Models for AI integration. Ensure compliance with government standards and security protocols. Collaborate with senior stakeholders to align AI strategy with business goals. Contribute to reusable architecture patterns and internal capability uplift. Mentor teams and support cross-government alignment of AI initiatives. Required Experience & Skills Proven experience scaling AI solutions in complex, regulated environments. Deep understanding of the AI/ML lifecycle, model governance, and ethical AI. Hands-on experience with platforms such as AWS Bedrock, Azure AI Foundry, Google Vertex, and open-source AI/ML stacks. Familiarity with Agentic AI Frameworks and risk-based AI assurance. Strong grasp of DPIAs, data protection, and transparency requirements. Excellent communication skills for engaging with senior stakeholders and multidisciplinary teams. Background in regulated environments with the ability to translate complex requirements into deliverable solutions. Additional Criteria Direct authorship of solution design documentation. Experience in developing architectural guardrails and technical standards. Hands-on delivery of AI solutions - not just oversight. Preference for candidates with a "doer" mindset - technically capable and execution-focused. People Source Consulting Ltd is acting as an Employment Business in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas.
We have a current opportunity for a Contract Agentic AI Technical Lead on a contract basis. The position will be HYBRID and require travel to Bristol occasionally. For further information about this position please apply. Agentic AI Technical Lead We require a C4/SM to support the delivery of Agentic & GenAI Products in the MOD Account. The role is predominantly working within Azure and embedded within a mature AI Factory. Deep technical understanding of GenAI tools, such as GPT models, and Agentic AI frameworks, such as Langgraph & Langchain, required. Strong full stack / software engineering skills also preferable. To provide technical leadership for a team of 15 Capgemini Invent technical developers across data science, software engineering and agentic AI. Technical Leadership: Act as the primary SME in your specialist domain, providing technical direction, guidance, and best practices to the team and wider organisation. Solution Design: Lead the design and architecture of solutions within your area of expertise, ensuring scalability, security, and alignment with business goals. Delivery Oversight: Support delivery teams by reviewing designs, code, and technical decisions to maintain quality and consistency. Knowledge Sharing: Mentor engineers, upskill team members, and foster a culture of technical excellence and continuous learning. Stakeholder Engagement: Translate complex technical concepts into business language, advising leadership, product owners, and clients. Governance & Standards: Define, champion, and enforce standards, patterns, and frameworks relevant to your domain. Problem Solving: Act as an escalation point for complex issues, ensuring rapid resolution and informed decision-making. Cross Discipline Collaboration: Work closely with product, design, and operations teams to ensure seamless delivery and operational readiness. Innovation & R&D: Stay ahead of emerging trends, tools, and methods in your specialist field; introduce innovations that add value to products, services, or client solutions. Please click here to find out more about our Key Information Documents. Please note that the documents provided contain generic information. If we are successful in finding you an assignment, you will receive a Key Information Document which will be specific to the vendor set-up you have chosen and your placement. To find out more about Computer Futures please visit (url removed) Computer Futures, a trading division of SThree Partnership LLP is acting as an Employment Business in relation to this vacancy Registered office 8 Bishopsgate, London, EC2N 4BQ, United Kingdom Partnership Number OC(phone number removed) England and Wales
Dec 19, 2025
Contractor
We have a current opportunity for a Contract Agentic AI Technical Lead on a contract basis. The position will be HYBRID and require travel to Bristol occasionally. For further information about this position please apply. Agentic AI Technical Lead We require a C4/SM to support the delivery of Agentic & GenAI Products in the MOD Account. The role is predominantly working within Azure and embedded within a mature AI Factory. Deep technical understanding of GenAI tools, such as GPT models, and Agentic AI frameworks, such as Langgraph & Langchain, required. Strong full stack / software engineering skills also preferable. To provide technical leadership for a team of 15 Capgemini Invent technical developers across data science, software engineering and agentic AI. Technical Leadership: Act as the primary SME in your specialist domain, providing technical direction, guidance, and best practices to the team and wider organisation. Solution Design: Lead the design and architecture of solutions within your area of expertise, ensuring scalability, security, and alignment with business goals. Delivery Oversight: Support delivery teams by reviewing designs, code, and technical decisions to maintain quality and consistency. Knowledge Sharing: Mentor engineers, upskill team members, and foster a culture of technical excellence and continuous learning. Stakeholder Engagement: Translate complex technical concepts into business language, advising leadership, product owners, and clients. Governance & Standards: Define, champion, and enforce standards, patterns, and frameworks relevant to your domain. Problem Solving: Act as an escalation point for complex issues, ensuring rapid resolution and informed decision-making. Cross Discipline Collaboration: Work closely with product, design, and operations teams to ensure seamless delivery and operational readiness. Innovation & R&D: Stay ahead of emerging trends, tools, and methods in your specialist field; introduce innovations that add value to products, services, or client solutions. Please click here to find out more about our Key Information Documents. Please note that the documents provided contain generic information. If we are successful in finding you an assignment, you will receive a Key Information Document which will be specific to the vendor set-up you have chosen and your placement. To find out more about Computer Futures please visit (url removed) Computer Futures, a trading division of SThree Partnership LLP is acting as an Employment Business in relation to this vacancy Registered office 8 Bishopsgate, London, EC2N 4BQ, United Kingdom Partnership Number OC(phone number removed) England and Wales
Our client are looking for a forward deployed engineer to spearhead our Palantir practice, delivering transformative decision intelligence solutions for major European enterprises. Combine deep technical expertise with strategic client partnership whilst building world-class capability within our team. Lead end-to-end Palantir implementations from discovery through to production deployment, taking ownership of technical architecture decisions and implementation quality Design and deliver high-impact bootcamps that prove value quickly, converting sceptics into advocates through compelling demonstrations of the platform's transformative potential Navigate complex enterprise environments to identify and prioritise use cases that deliver the highest business value, working from first principles to understand true organisational needs rather than stated requirements Articulate Palantir's value proposition to C-suite audiences, translating technical capabilities into business outcomes they care about Skills 5-8+ years as Palantir focussed Forward Deployed Engineer with demonstrable progression to enterprise leadership roles or complex technical implementations Enterprise-scale battle scars - you've worked on implementations large enough to trigger multiple failure modes, ideally at companies where Palantir has become mission-critical (reference examples: major aerospace, mining, insurance, healthcare systems, or government programmes) Deep Foundry technical expertise across the full stack: Pipeline Builder, Ontology, Workshop, OSDK, Code Repositories, Actions, and AIP/agentic capabilities - you can build production-grade applications not just prototypes Production deployment experience including performance optimisation, data pipeline architecture, permissioning at scale, audit requirements, and operational maintenance
Dec 19, 2025
Full time
Our client are looking for a forward deployed engineer to spearhead our Palantir practice, delivering transformative decision intelligence solutions for major European enterprises. Combine deep technical expertise with strategic client partnership whilst building world-class capability within our team. Lead end-to-end Palantir implementations from discovery through to production deployment, taking ownership of technical architecture decisions and implementation quality Design and deliver high-impact bootcamps that prove value quickly, converting sceptics into advocates through compelling demonstrations of the platform's transformative potential Navigate complex enterprise environments to identify and prioritise use cases that deliver the highest business value, working from first principles to understand true organisational needs rather than stated requirements Articulate Palantir's value proposition to C-suite audiences, translating technical capabilities into business outcomes they care about Skills 5-8+ years as Palantir focussed Forward Deployed Engineer with demonstrable progression to enterprise leadership roles or complex technical implementations Enterprise-scale battle scars - you've worked on implementations large enough to trigger multiple failure modes, ideally at companies where Palantir has become mission-critical (reference examples: major aerospace, mining, insurance, healthcare systems, or government programmes) Deep Foundry technical expertise across the full stack: Pipeline Builder, Ontology, Workshop, OSDK, Code Repositories, Actions, and AIP/agentic capabilities - you can build production-grade applications not just prototypes Production deployment experience including performance optimisation, data pipeline architecture, permissioning at scale, audit requirements, and operational maintenance
Our client are a private equity backed firm who are looking for a deep AI/Agentic Engineer to lead the design and delivery of the organisations complex AI-native engagements, from agentic systems to semantic layers. Pair hands-on technical leadership with client trust, shaping both enterprise outcomes and the firm's long-term engineering capability. Responsibilities: You will design and build production-grade AI systems across: LLM applications using modern orchestration patterns, prompt frameworks, and evaluation loops. Multi-agent architectures , including planning, delegation, safety constraints, and monitoring. Retrieval & vector-based systems , embeddings, structured reasoning, and semantic workflows. Ontology & knowledge modelling literacy , enabling more precise reasoning and data alignment. Integrations & automation , including API workflows, tools, and enterprise connectors. Skills: 6-8 years in Software/application engineering, AI engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ability to build production-grade workflows. Experience with at least one cloud AI ecosystem (Azure/OpenAI, GCP/Vertex, Anthropic, AWS etc.). Familiarity with semantic modelling, ontologies, or knowledge graph thinking - literacy required, mastery a bonus.
Dec 19, 2025
Full time
Our client are a private equity backed firm who are looking for a deep AI/Agentic Engineer to lead the design and delivery of the organisations complex AI-native engagements, from agentic systems to semantic layers. Pair hands-on technical leadership with client trust, shaping both enterprise outcomes and the firm's long-term engineering capability. Responsibilities: You will design and build production-grade AI systems across: LLM applications using modern orchestration patterns, prompt frameworks, and evaluation loops. Multi-agent architectures , including planning, delegation, safety constraints, and monitoring. Retrieval & vector-based systems , embeddings, structured reasoning, and semantic workflows. Ontology & knowledge modelling literacy , enabling more precise reasoning and data alignment. Integrations & automation , including API workflows, tools, and enterprise connectors. Skills: 6-8 years in Software/application engineering, AI engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ability to build production-grade workflows. Experience with at least one cloud AI ecosystem (Azure/OpenAI, GCP/Vertex, Anthropic, AWS etc.). Familiarity with semantic modelling, ontologies, or knowledge graph thinking - literacy required, mastery a bonus.
AI Evangelist - Financial Services (12-Month Contract) Location: Blackfriars, London (Onsite, 5 days per week) Contract: Inside IR35 Rate: 800 per day Duration: 12 months Role Overview We are seeking an AI Evangelist with strong financial services experience to lead the adoption and integration of advanced AI solutions across banking, trading, and insurance environments. This role combines technical leadership, strategic advisory, and thought leadership to deliver AI-driven transformation in highly regulated, mission-critical settings. Key Responsibilities Financial AI Solutions: Design and implement AI-powered applications for investment banking, trading platforms, and insurance workflows. Business Translation: Convert complex AI concepts into actionable insights for technical teams and senior executives in financial contexts. Enablement & Training: Deliver workshops and training sessions focused on AI adoption within banking and insurance operations. Thought Leadership: Produce technical blogs, white papers, and internal documentation showcasing AI's impact on financial innovation. Strategic Advisory: Advise C-level executives and heads of engineering/architecture on AI strategy aligned with financial regulations. Industry Engagement: Represent the organization at finance-focused conferences and forums to promote responsible AI adoption. Compliance Alignment: Ensure all AI solutions meet strict regulatory, risk, and ethical standards in financial services. Prototyping & Deployment: Build and deploy AI models for market forecasting, risk analytics, automated underwriting, and AML detection. Technical Leadership Architect and implement agent-based AI systems and generative code workflows for financial applications. Oversee design reviews and code quality for AI-assisted development, maintaining best practices in Python and other languages. Establish robust testing and validation frameworks for AI-generated code, including prompt engineering and compliance checks. Mentor engineering teams and set standards for mixed human/AI development environments. Collaborate with DevOps, security, and product teams to accelerate safe adoption of AI-driven features. Essential Qualifications Degree in Computer Science, Data Science, Finance, or related discipline. Proven experience in financial services or fintech -ideally within investment banking, trading, or insurance. Strong programming skills in Python, plus experience with languages such as Java, C++, or Go. Familiarity with modern UI frameworks (TypeScript, Node.js). Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch) applied to financial datasets. Minimum 4 years in AI-focused roles within finance or technical consulting, with exposure to regulatory compliance. Deep understanding of AI ethics, governance, and data privacy in regulated environments. Exceptional communication and stakeholder engagement skills. Preferred Skills Expertise in prompt engineering, context management, and fine-tuning techniques (LoRA/QLoRA). Experience building RAG pipelines and agentic workflows for enterprise financial applications. Knowledge of vector databases (FAISS, Pinecone, Weaviate) and graph technologies (Neo4j). Familiarity with observability tools and AI evaluation frameworks. Strong grasp of containerization and cloud deployment (Docker, AWS, Azure). Tools & Platforms GitHub Copilot, ChatGPT/GPT-4, Claude for AI-assisted development. LangChain, LlamaIndex for RAG implementations. SonarQube for code security and quality assurance. Jira with AI plugins for agile delivery. Monitoring tools like Datadog and Dynatrace for production reliability. Ideal Candidate Traits Analytical and innovative mindset with a passion for AI-driven transformation in finance. Skilled communicator who can bridge technical and business perspectives. Advocate for ethical AI practices and secure deployment in mission-critical financial environments.
Dec 19, 2025
Contractor
AI Evangelist - Financial Services (12-Month Contract) Location: Blackfriars, London (Onsite, 5 days per week) Contract: Inside IR35 Rate: 800 per day Duration: 12 months Role Overview We are seeking an AI Evangelist with strong financial services experience to lead the adoption and integration of advanced AI solutions across banking, trading, and insurance environments. This role combines technical leadership, strategic advisory, and thought leadership to deliver AI-driven transformation in highly regulated, mission-critical settings. Key Responsibilities Financial AI Solutions: Design and implement AI-powered applications for investment banking, trading platforms, and insurance workflows. Business Translation: Convert complex AI concepts into actionable insights for technical teams and senior executives in financial contexts. Enablement & Training: Deliver workshops and training sessions focused on AI adoption within banking and insurance operations. Thought Leadership: Produce technical blogs, white papers, and internal documentation showcasing AI's impact on financial innovation. Strategic Advisory: Advise C-level executives and heads of engineering/architecture on AI strategy aligned with financial regulations. Industry Engagement: Represent the organization at finance-focused conferences and forums to promote responsible AI adoption. Compliance Alignment: Ensure all AI solutions meet strict regulatory, risk, and ethical standards in financial services. Prototyping & Deployment: Build and deploy AI models for market forecasting, risk analytics, automated underwriting, and AML detection. Technical Leadership Architect and implement agent-based AI systems and generative code workflows for financial applications. Oversee design reviews and code quality for AI-assisted development, maintaining best practices in Python and other languages. Establish robust testing and validation frameworks for AI-generated code, including prompt engineering and compliance checks. Mentor engineering teams and set standards for mixed human/AI development environments. Collaborate with DevOps, security, and product teams to accelerate safe adoption of AI-driven features. Essential Qualifications Degree in Computer Science, Data Science, Finance, or related discipline. Proven experience in financial services or fintech -ideally within investment banking, trading, or insurance. Strong programming skills in Python, plus experience with languages such as Java, C++, or Go. Familiarity with modern UI frameworks (TypeScript, Node.js). Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch) applied to financial datasets. Minimum 4 years in AI-focused roles within finance or technical consulting, with exposure to regulatory compliance. Deep understanding of AI ethics, governance, and data privacy in regulated environments. Exceptional communication and stakeholder engagement skills. Preferred Skills Expertise in prompt engineering, context management, and fine-tuning techniques (LoRA/QLoRA). Experience building RAG pipelines and agentic workflows for enterprise financial applications. Knowledge of vector databases (FAISS, Pinecone, Weaviate) and graph technologies (Neo4j). Familiarity with observability tools and AI evaluation frameworks. Strong grasp of containerization and cloud deployment (Docker, AWS, Azure). Tools & Platforms GitHub Copilot, ChatGPT/GPT-4, Claude for AI-assisted development. LangChain, LlamaIndex for RAG implementations. SonarQube for code security and quality assurance. Jira with AI plugins for agile delivery. Monitoring tools like Datadog and Dynatrace for production reliability. Ideal Candidate Traits Analytical and innovative mindset with a passion for AI-driven transformation in finance. Skilled communicator who can bridge technical and business perspectives. Advocate for ethical AI practices and secure deployment in mission-critical financial environments.
Role: AI Evangelist (Hands-On) A senior technical and advocacy role focused on bridging advanced AI technologies with practical business needs in a financial organisation. The position combines hands-on development with stakeholder education and strategic influence. Core Responsibilities Build and demonstrate AI-powered solutions for financial applications (e.g., trading, investment banking, insurance). Translate complex AI concepts into business value for technical and non-technical stakeholders. Conduct workshops and training to promote AI literacy and upskill teams. Author technical blogs, white papers, and internal documentation. Advise senior leadership on AI strategies and compliance. Represent the organization at industry events and forums. Ensure AI solutions meet regulatory and ethical standards. Prototype and deploy AI models for forecasting, customer insights, underwriting, and fraud detection. Technical Responsibilities Design and manage agentic AI architectures and generative code systems. Oversee code reviews and maintain standards for AI-assisted development. Develop testing and validation protocols for AI-generated code. Mentor technical teams and establish best practices. Collaborate with cross-functional teams for safe AI adoption. Qualifications Degree in Computer Science, Data Science, Finance, or related field. Strong programming skills (Python, SQL, C++, Java, etc.). Experience with AI/ML frameworks (TensorFlow, PyTorch). Minimum 4+ years in AI roles within finance or consulting. Knowledge of AI ethics, compliance, and data privacy. Excellent communication and stakeholder engagement skills. Desired Traits Passion for innovation in regulated environments. Strong problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance in AI systems. Experience with containerization and cloud deployments. 5 Days on-site in the London Office (Blackfriars) Inside IR35 12 month contract Please send me a copy of your CV if you're interested
Dec 19, 2025
Contractor
Role: AI Evangelist (Hands-On) A senior technical and advocacy role focused on bridging advanced AI technologies with practical business needs in a financial organisation. The position combines hands-on development with stakeholder education and strategic influence. Core Responsibilities Build and demonstrate AI-powered solutions for financial applications (e.g., trading, investment banking, insurance). Translate complex AI concepts into business value for technical and non-technical stakeholders. Conduct workshops and training to promote AI literacy and upskill teams. Author technical blogs, white papers, and internal documentation. Advise senior leadership on AI strategies and compliance. Represent the organization at industry events and forums. Ensure AI solutions meet regulatory and ethical standards. Prototype and deploy AI models for forecasting, customer insights, underwriting, and fraud detection. Technical Responsibilities Design and manage agentic AI architectures and generative code systems. Oversee code reviews and maintain standards for AI-assisted development. Develop testing and validation protocols for AI-generated code. Mentor technical teams and establish best practices. Collaborate with cross-functional teams for safe AI adoption. Qualifications Degree in Computer Science, Data Science, Finance, or related field. Strong programming skills (Python, SQL, C++, Java, etc.). Experience with AI/ML frameworks (TensorFlow, PyTorch). Minimum 4+ years in AI roles within finance or consulting. Knowledge of AI ethics, compliance, and data privacy. Excellent communication and stakeholder engagement skills. Desired Traits Passion for innovation in regulated environments. Strong problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance in AI systems. Experience with containerization and cloud deployments. 5 Days on-site in the London Office (Blackfriars) Inside IR35 12 month contract Please send me a copy of your CV if you're interested
AI Evangelist - Inside IR35 - Hybrid Role Overview The Senior AI Evangelist plays a pivotal hands-on role in shaping and driving the responsible adoption of Artificial Intelligence across the organization. This position bridges the gap between cutting-edge AI technologies and real-world financial business needs, influencing both strategy and execution. The role requires deep technical expertise, exceptional communication skills, and a passion for translating AI innovation into meaningful business impact across investment banking, trading, insurance, and broader financial ecosystems. Key Responsibilities - Evangelism & Strategy Solution Innovation: Build and demonstrate AI-powered solutions tailored to financial applications, including use cases in investment banking, trading, and insurance. AI Storytelling: Translate complex AI concepts into clear, actionable business value for both technical and non-technical stakeholders, including executive leadership. Education & Enablement: Lead workshops, seminars, and training sessions to improve AI literacy and upskill teams across banking, investment, or insurance environments. Executive Advisory: Provide advisory-level guidance to CxOs, Heads of Engineering, and Heads of Architecture on AI strategy, enterprise architecture, and emerging technology trends. Industry Influence: Represent the organization at conferences, webinars, and industry forums to position the firm as a leader in responsible AI adoption in finance. Regulatory Alignment: Collaborate with compliance, risk, and IT teams to ensure AI solutions adhere to stringent financial-sector regulatory, ethical, and governance standards. AI Model Deployment: Prototype, test, and deploy AI systems for use cases such as market forecasting, customer insights, automated underwriting, fraud detection, and anti-money laundering (AML). Key Technical & Design Responsibilities Agentic & Generative AI Architectures: Build, deploy, and manage agentic AI systems and generative code workflows using LLMs, automation agents, and code generation tools within secure production environments. Technical Leadership: Oversee solution design, implementation, and code reviews-particularly for code created or augmented by AI-to ensure security, scalability, and maintainability across Python and other languages. AI Reliability & Governance: Develop and maintain rigorous testing/validation frameworks for AI-generated code, agent behavior, prompts, and model outputs, including monitoring for anomalies and compliance risks. Cross-Functional Collaboration: Work closely with DevOps, Security, Product, and Business teams to drive rapid, safe integration of agentic and generative AI features into enterprise systems. Essential Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Finance, or a related field. Experience with high-level programming languages such as C++, Java, or C#. Proficiency with TypeScript, Node.js, and modern JavaScript frameworks for UI development. Strong hands-on experience with Python, SQL, and AI/ML frameworks (e.g., TensorFlow, PyTorch), particularly within financial workflows. To apply for this role please submit your CV or contact Dillon Blackburn on (phone number removed) or at (url removed). Tenth Revolution Group are the go-to recruiter for Data & AI roles in the UK offering more opportunities across the country than any other recruitment agency. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, and the London Fabric User Group. We are the global leaders in Data & AI recruitment.
Dec 19, 2025
Contractor
AI Evangelist - Inside IR35 - Hybrid Role Overview The Senior AI Evangelist plays a pivotal hands-on role in shaping and driving the responsible adoption of Artificial Intelligence across the organization. This position bridges the gap between cutting-edge AI technologies and real-world financial business needs, influencing both strategy and execution. The role requires deep technical expertise, exceptional communication skills, and a passion for translating AI innovation into meaningful business impact across investment banking, trading, insurance, and broader financial ecosystems. Key Responsibilities - Evangelism & Strategy Solution Innovation: Build and demonstrate AI-powered solutions tailored to financial applications, including use cases in investment banking, trading, and insurance. AI Storytelling: Translate complex AI concepts into clear, actionable business value for both technical and non-technical stakeholders, including executive leadership. Education & Enablement: Lead workshops, seminars, and training sessions to improve AI literacy and upskill teams across banking, investment, or insurance environments. Executive Advisory: Provide advisory-level guidance to CxOs, Heads of Engineering, and Heads of Architecture on AI strategy, enterprise architecture, and emerging technology trends. Industry Influence: Represent the organization at conferences, webinars, and industry forums to position the firm as a leader in responsible AI adoption in finance. Regulatory Alignment: Collaborate with compliance, risk, and IT teams to ensure AI solutions adhere to stringent financial-sector regulatory, ethical, and governance standards. AI Model Deployment: Prototype, test, and deploy AI systems for use cases such as market forecasting, customer insights, automated underwriting, fraud detection, and anti-money laundering (AML). Key Technical & Design Responsibilities Agentic & Generative AI Architectures: Build, deploy, and manage agentic AI systems and generative code workflows using LLMs, automation agents, and code generation tools within secure production environments. Technical Leadership: Oversee solution design, implementation, and code reviews-particularly for code created or augmented by AI-to ensure security, scalability, and maintainability across Python and other languages. AI Reliability & Governance: Develop and maintain rigorous testing/validation frameworks for AI-generated code, agent behavior, prompts, and model outputs, including monitoring for anomalies and compliance risks. Cross-Functional Collaboration: Work closely with DevOps, Security, Product, and Business teams to drive rapid, safe integration of agentic and generative AI features into enterprise systems. Essential Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Finance, or a related field. Experience with high-level programming languages such as C++, Java, or C#. Proficiency with TypeScript, Node.js, and modern JavaScript frameworks for UI development. Strong hands-on experience with Python, SQL, and AI/ML frameworks (e.g., TensorFlow, PyTorch), particularly within financial workflows. To apply for this role please submit your CV or contact Dillon Blackburn on (phone number removed) or at (url removed). Tenth Revolution Group are the go-to recruiter for Data & AI roles in the UK offering more opportunities across the country than any other recruitment agency. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, and the London Fabric User Group. We are the global leaders in Data & AI recruitment.
Lead Full Stack Developer (AI Solutions) Remote with trips to client sites 1-2 times a month - Cheshire £70,000 - £80,000 + benefits Tech: C# .NET Core Azure React RAG Agentic AI Azure Foundry/Microsoft Foundry Build AI that's already live - and actually used We're hiring a Lead Full Stack Developer to join a market-leading company delivering production-ready Generative AI solutions for UK local governments . This is not experimental AI or endless POCs. With 20+ councils live today, the platform already powers: AI Contact Centres Staff Copilots Social Care AI Assistants AI Readiness & Assessment tooling The business is now investing heavily in scale - and this role sits at the heart of that growth. The role This is a hands-on, Back End-focused lead engineer role with real technical ownership. You won't be a people manager - instead, you'll act as the technical anchor between clients, product, and delivery teams: Leading solution design and implementation Translating real-world public sector workflows into scalable AI systems Mentoring engineers and setting technical standards Building and shipping AI-first features in production You'll work in small SCRUM teams, directly contributing code while coordinating work across multiple developers and collaborating closely with Product Owners, Architects, BAs, and Delivery leadership. Key Responsibilities Engage directly with client stakeholders to capture and document business process requirements Translate workflows into technical designs, backlog items, and deliverables Assess the feasibility and viability of solutions against business needs, budgets, and technical constraints Provide technical leadership across programmes and projects, coordinating outputs across delivery teams Actively contribute to hands-on software development in .NET, C#, Azure, REACT, and related technologies Implement AI features using LLMs, RAG, Agentic AI, and related frameworks Mentor and support developers, ensuring coding standards and best practices are applied consistently Lead backlog refinement, sprint planning, and technical prioritisation activities Oversee code reviews, unit testing, and QA to maintain delivery quality Support cloud-first delivery across Azure, Power Platform, and M365 Required Skills and Experience Strong commercial experience with C# and .NET Core in production environments Solid background delivering Azure-based solutions Hands-on experience implementing Generative AI features (LLMs, RAG, Agentic AI) - POC or production Experience working in both product-led and client-facing delivery environments Proven ability to translate business requirements into scalable technical solutions Experience mentoring or guiding developers (without line management) Confident communicator, comfortable working with non-technical stakeholders Nice to have Azure, .NET, or related professional certifications Experience in public sector, regulated environments, or complex stakeholder landscapes Why this is a great opportunity Live AI platform with real users and real impact Clear product-market fit and growing customer base Modern AI stack - not hype, not research, not endless pilots Senior technical influence without people management burden Remote-first with a collaborative, delivery-focused engineering culture
Dec 18, 2025
Full time
Lead Full Stack Developer (AI Solutions) Remote with trips to client sites 1-2 times a month - Cheshire £70,000 - £80,000 + benefits Tech: C# .NET Core Azure React RAG Agentic AI Azure Foundry/Microsoft Foundry Build AI that's already live - and actually used We're hiring a Lead Full Stack Developer to join a market-leading company delivering production-ready Generative AI solutions for UK local governments . This is not experimental AI or endless POCs. With 20+ councils live today, the platform already powers: AI Contact Centres Staff Copilots Social Care AI Assistants AI Readiness & Assessment tooling The business is now investing heavily in scale - and this role sits at the heart of that growth. The role This is a hands-on, Back End-focused lead engineer role with real technical ownership. You won't be a people manager - instead, you'll act as the technical anchor between clients, product, and delivery teams: Leading solution design and implementation Translating real-world public sector workflows into scalable AI systems Mentoring engineers and setting technical standards Building and shipping AI-first features in production You'll work in small SCRUM teams, directly contributing code while coordinating work across multiple developers and collaborating closely with Product Owners, Architects, BAs, and Delivery leadership. Key Responsibilities Engage directly with client stakeholders to capture and document business process requirements Translate workflows into technical designs, backlog items, and deliverables Assess the feasibility and viability of solutions against business needs, budgets, and technical constraints Provide technical leadership across programmes and projects, coordinating outputs across delivery teams Actively contribute to hands-on software development in .NET, C#, Azure, REACT, and related technologies Implement AI features using LLMs, RAG, Agentic AI, and related frameworks Mentor and support developers, ensuring coding standards and best practices are applied consistently Lead backlog refinement, sprint planning, and technical prioritisation activities Oversee code reviews, unit testing, and QA to maintain delivery quality Support cloud-first delivery across Azure, Power Platform, and M365 Required Skills and Experience Strong commercial experience with C# and .NET Core in production environments Solid background delivering Azure-based solutions Hands-on experience implementing Generative AI features (LLMs, RAG, Agentic AI) - POC or production Experience working in both product-led and client-facing delivery environments Proven ability to translate business requirements into scalable technical solutions Experience mentoring or guiding developers (without line management) Confident communicator, comfortable working with non-technical stakeholders Nice to have Azure, .NET, or related professional certifications Experience in public sector, regulated environments, or complex stakeholder landscapes Why this is a great opportunity Live AI platform with real users and real impact Clear product-market fit and growing customer base Modern AI stack - not hype, not research, not endless pilots Senior technical influence without people management burden Remote-first with a collaborative, delivery-focused engineering culture
Role Title: Graduate Data Engineer Contract: 12 months Location: Marlow (hybrid) SRG are working with a leading pharmaceutical company based in Marlow. Our client develops and manufacture an impressive portfolio of aesthetics brands and products. Our client is committed to driving innovation and providing high-quality products and services. Role Overview As a Graduate Data Engineer, you will build and maintain scalable data pipelines in Palantir Foundry for advanced reporting and analytics while collaborating with cross-functional teams as part of the BTS Data & Analytics team. You will work closely with key stakeholders in Engineering, Product, GTM, and other groups to help build scalable data solutions that support key metrics, reporting, and insights. You will assist in ensuring teams have access to reliable, accurate data as our company grows. You will have the opportunity to support projects that enable self-serve insights, helping teams make data-driven decisions, while learning from experienced team members and developing your technical and business skills. Key Responsibilities: Build and maintain data pipelines, leveraging PySpark and/or Typescript within Foundry, to transform raw data into reliable, usable datasets. Familiarity with Palantir Foundry, PySpark, Kafka, TypeScript, PowerBI preferable. Assist in preparing and optimizing data pipelines to support machine learning and AI model development, ensuring datasets are clean, well-structured, and readily usable by Data Science teams. Support the integration and management of feature engineering processes and model outputs into Foundry's data ecosystem, helping enable scalable deployment and monitoring of AI/ML solutions as you develop your skills in this area. Engaged in gathering and translating stakeholder requirements for key data models and reporting, with a focus on Palantir Foundry workflows and tools. Participate in developing and refining dashboards and reports in Foundry to visualize key metrics and insights as you grow your data visualization skills. Collaborate with Product, Engineering, and GTM teams to align data architecture and solutions, learning to support scalable, self-serve analytics across the organization. Have some prompt engineering experience with large language models, including writing and evaluating complex multi-step prompts Continuously develop your understanding of the company's data landscape, including Palantir Foundry's ontology-driven approach and best practices for data management. About you: You have a degree in Computer Science, Engineering, Mathematics, or similar, or have similar work experience. Having up to 2 years of experience building data pipelines at work or through internships is helpful. You can write clear and reliable Python/PySpark code. You are familiar with popular analytics tools (like pandas, numpy, matplotlib), big data frameworks (like Spark), and cloud services (like Palantir, AWS, Azure, or Google Cloud). You have a deep understanding of data models, relational and non-relational databases, and how they are used to organize, store, and retrieve data efficiently for analytics and machine learning. Knowing about software engineering methods, including DevOps, DataOps, or MLOps, is also a plus. You will be considered a strong fit if you have: Master's degree in engineering (such as AI/ML, Data Systems, Computer Science, Mathematics, Biotechnology, Physics), or minimum 2 years of relevant technology experience. Experience with Generative AI (GenAI) and agentic systems will be considered a strong plus. Have a proactive and adaptable mindset: willing to take initiative, learn new skills, and contribute to different aspects of a project as needed to drive solutions from start to finish, even beyond the formal job description. Show a strong ability to thrive in situations of ambiguity, taking initiative to create clarity for yourself and the team, and proactively driving progress even when details are uncertain or evolving. Other details: Hybrid working policy: Currently, our client expects all staff to be in their Marlow-based office at least 3 days a week from Jan 2026. No visa sponsorship. ILR/Citizenship required. Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.
Dec 18, 2025
Seasonal
Role Title: Graduate Data Engineer Contract: 12 months Location: Marlow (hybrid) SRG are working with a leading pharmaceutical company based in Marlow. Our client develops and manufacture an impressive portfolio of aesthetics brands and products. Our client is committed to driving innovation and providing high-quality products and services. Role Overview As a Graduate Data Engineer, you will build and maintain scalable data pipelines in Palantir Foundry for advanced reporting and analytics while collaborating with cross-functional teams as part of the BTS Data & Analytics team. You will work closely with key stakeholders in Engineering, Product, GTM, and other groups to help build scalable data solutions that support key metrics, reporting, and insights. You will assist in ensuring teams have access to reliable, accurate data as our company grows. You will have the opportunity to support projects that enable self-serve insights, helping teams make data-driven decisions, while learning from experienced team members and developing your technical and business skills. Key Responsibilities: Build and maintain data pipelines, leveraging PySpark and/or Typescript within Foundry, to transform raw data into reliable, usable datasets. Familiarity with Palantir Foundry, PySpark, Kafka, TypeScript, PowerBI preferable. Assist in preparing and optimizing data pipelines to support machine learning and AI model development, ensuring datasets are clean, well-structured, and readily usable by Data Science teams. Support the integration and management of feature engineering processes and model outputs into Foundry's data ecosystem, helping enable scalable deployment and monitoring of AI/ML solutions as you develop your skills in this area. Engaged in gathering and translating stakeholder requirements for key data models and reporting, with a focus on Palantir Foundry workflows and tools. Participate in developing and refining dashboards and reports in Foundry to visualize key metrics and insights as you grow your data visualization skills. Collaborate with Product, Engineering, and GTM teams to align data architecture and solutions, learning to support scalable, self-serve analytics across the organization. Have some prompt engineering experience with large language models, including writing and evaluating complex multi-step prompts Continuously develop your understanding of the company's data landscape, including Palantir Foundry's ontology-driven approach and best practices for data management. About you: You have a degree in Computer Science, Engineering, Mathematics, or similar, or have similar work experience. Having up to 2 years of experience building data pipelines at work or through internships is helpful. You can write clear and reliable Python/PySpark code. You are familiar with popular analytics tools (like pandas, numpy, matplotlib), big data frameworks (like Spark), and cloud services (like Palantir, AWS, Azure, or Google Cloud). You have a deep understanding of data models, relational and non-relational databases, and how they are used to organize, store, and retrieve data efficiently for analytics and machine learning. Knowing about software engineering methods, including DevOps, DataOps, or MLOps, is also a plus. You will be considered a strong fit if you have: Master's degree in engineering (such as AI/ML, Data Systems, Computer Science, Mathematics, Biotechnology, Physics), or minimum 2 years of relevant technology experience. Experience with Generative AI (GenAI) and agentic systems will be considered a strong plus. Have a proactive and adaptable mindset: willing to take initiative, learn new skills, and contribute to different aspects of a project as needed to drive solutions from start to finish, even beyond the formal job description. Show a strong ability to thrive in situations of ambiguity, taking initiative to create clarity for yourself and the team, and proactively driving progress even when details are uncertain or evolving. Other details: Hybrid working policy: Currently, our client expects all staff to be in their Marlow-based office at least 3 days a week from Jan 2026. No visa sponsorship. ILR/Citizenship required. Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.
Lead AI Engineer Tech Focus: Microsoft Azure AI Stack / LLM / Agent Orchestration / Agentic AI / Data Science Salary: 90,000 - 100,000 + 20% Bonus + 20% Employer Pension Contribution Location: London - Hybrid This is an exciting opportunity for a Lead AI Engineer to join a prestigious financial organisation as they launch a major AI initiative. Having completed their digital and data transformation programme, the organisation now operates fully in Azure Cloud and is making significant strides in AI adoption. They've built an AI platform designed to improve efficiency for both internal and external facing users. This is a hands-on technical leadership role. You'll lead projects and mentor engineers while actively developing Azure-native agent frameworks and building team-specific AI applications that deliver business outcomes. You'll work in a cross-functional team alongside an AI Engineering Manager, Architect, DevOps Engineers, AI Test Lead, Data Scientists, and Project Managers. What we're looking for: Hands-on AI development experience in a cloud environment (ideally Azure AI Stack, but open to other platforms) Proven experience in a lead or principal capacity (technical leadership, project ownership, mentoring) Practical experience with Large Language Models (LLMs) in production environments Experience with Agent Orchestration and building frameworks that deliver business outcomes Strong coding skills in Python and SQL Desirable: Background in Data Science Light front-end development, for example being able to create internal web applications If you're passionate about building practical AI solutions and want to work in a collaborative environment that takes AI seriously, please apply directly and we'll be in touch with more details.
Dec 18, 2025
Full time
Lead AI Engineer Tech Focus: Microsoft Azure AI Stack / LLM / Agent Orchestration / Agentic AI / Data Science Salary: 90,000 - 100,000 + 20% Bonus + 20% Employer Pension Contribution Location: London - Hybrid This is an exciting opportunity for a Lead AI Engineer to join a prestigious financial organisation as they launch a major AI initiative. Having completed their digital and data transformation programme, the organisation now operates fully in Azure Cloud and is making significant strides in AI adoption. They've built an AI platform designed to improve efficiency for both internal and external facing users. This is a hands-on technical leadership role. You'll lead projects and mentor engineers while actively developing Azure-native agent frameworks and building team-specific AI applications that deliver business outcomes. You'll work in a cross-functional team alongside an AI Engineering Manager, Architect, DevOps Engineers, AI Test Lead, Data Scientists, and Project Managers. What we're looking for: Hands-on AI development experience in a cloud environment (ideally Azure AI Stack, but open to other platforms) Proven experience in a lead or principal capacity (technical leadership, project ownership, mentoring) Practical experience with Large Language Models (LLMs) in production environments Experience with Agent Orchestration and building frameworks that deliver business outcomes Strong coding skills in Python and SQL Desirable: Background in Data Science Light front-end development, for example being able to create internal web applications If you're passionate about building practical AI solutions and want to work in a collaborative environment that takes AI seriously, please apply directly and we'll be in touch with more details.
Lead AI Engineer Tech Focus: Microsoft Azure AI Stack/LLM/Agent Orchestration/Agentic AI/Data Science Salary: £90,000 - £100,000 + 20% Bonus + 20% Employer Pension Contribution Location: London - Hybrid This is an exciting opportunity for a Lead AI Engineer to join a prestigious financial organisation as they launch a major AI initiative. Having completed their digital and data transformation programme, the organisation now operates fully in Azure Cloud and is making significant strides in AI adoption. They've built an AI platform designed to improve efficiency for both internal and external facing users. This is a hands-on technical leadership role. You'll lead projects and mentor engineers while actively developing Azure-native agent frameworks and building team-specific AI applications that deliver business outcomes. You'll work in a cross-functional team alongside an AI Engineering Manager, Architect, DevOps Engineers, AI Test Lead, Data Scientists, and Project Managers. What we're looking for: Hands-on AI development experience in a cloud environment (ideally Azure AI Stack, but open to other platforms) Proven experience in a lead or principal capacity (technical leadership, project ownership, mentoring) Practical experience with Large Language Models (LLMs) in production environments Experience with Agent Orchestration and building frameworks that deliver business outcomes Strong coding skills in Python and SQL Desirable: Background in Data Science Light Front End development, for example being able to create internal web applications If you're passionate about building practical AI solutions and want to work in a collaborative environment that takes AI seriously, please apply directly and we'll be in touch with more details.
Dec 17, 2025
Full time
Lead AI Engineer Tech Focus: Microsoft Azure AI Stack/LLM/Agent Orchestration/Agentic AI/Data Science Salary: £90,000 - £100,000 + 20% Bonus + 20% Employer Pension Contribution Location: London - Hybrid This is an exciting opportunity for a Lead AI Engineer to join a prestigious financial organisation as they launch a major AI initiative. Having completed their digital and data transformation programme, the organisation now operates fully in Azure Cloud and is making significant strides in AI adoption. They've built an AI platform designed to improve efficiency for both internal and external facing users. This is a hands-on technical leadership role. You'll lead projects and mentor engineers while actively developing Azure-native agent frameworks and building team-specific AI applications that deliver business outcomes. You'll work in a cross-functional team alongside an AI Engineering Manager, Architect, DevOps Engineers, AI Test Lead, Data Scientists, and Project Managers. What we're looking for: Hands-on AI development experience in a cloud environment (ideally Azure AI Stack, but open to other platforms) Proven experience in a lead or principal capacity (technical leadership, project ownership, mentoring) Practical experience with Large Language Models (LLMs) in production environments Experience with Agent Orchestration and building frameworks that deliver business outcomes Strong coding skills in Python and SQL Desirable: Background in Data Science Light Front End development, for example being able to create internal web applications If you're passionate about building practical AI solutions and want to work in a collaborative environment that takes AI seriously, please apply directly and we'll be in touch with more details.
Senior Machine Learning Engineer (Generative AI / LLMs) Location: Fully Remote (UK-based) Salary: 75,000 - 100,000 (depending on experience) The Role We're hiring a Senior Machine Learning Engineer to lead the design and productionisation of Generative AI and Large Language Model (LLM) applications. This role sits at the heart of an AI-focused engineering team, delivering scalable, production-grade systems using GCP and Google's AI ecosystem . You'll be a senior, hands-on engineer owning complex technical problems end to end, with a strong influence over architecture, tooling, and the future direction of LLM-powered products. What You'll Be Doing Design, develop, and deploy advanced machine learning and deep learning models into production. Architect scalable LLMOps pipelines on GCP / Vertex AI , including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop and deploy autonomous or semi-autonomous agents using modern agent frameworks and Google AI tooling. Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions. Monitor, optimise, and continuously improve models in live production environments. Contribute to the architecture and evolution of the AI platform and supporting data infrastructure. Stay current with emerging research, tools, and best practices across ML and Generative AI. What We're Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval-based architectures. Proven experience designing and operating large-scale ML systems in production . Strong experience with GCP Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with LLM evaluation frameworks such as RAGAS or TruLens . Experience fine-tuning large models or working with reinforcement learning techniques. Background in mathematics, statistics, or theoretical computer science. Understanding of data governance, bias mitigation, or model interpretability. Why Join Work on real, production-grade GenAI systems with clear business impact. High autonomy and ownership in a senior, hands-on engineering role. Fully remote working with a collaborative, distributed team. Opportunity to influence architecture and long-term technical direction. Competitive salary up to 100k , plus benefits.
Dec 17, 2025
Full time
Senior Machine Learning Engineer (Generative AI / LLMs) Location: Fully Remote (UK-based) Salary: 75,000 - 100,000 (depending on experience) The Role We're hiring a Senior Machine Learning Engineer to lead the design and productionisation of Generative AI and Large Language Model (LLM) applications. This role sits at the heart of an AI-focused engineering team, delivering scalable, production-grade systems using GCP and Google's AI ecosystem . You'll be a senior, hands-on engineer owning complex technical problems end to end, with a strong influence over architecture, tooling, and the future direction of LLM-powered products. What You'll Be Doing Design, develop, and deploy advanced machine learning and deep learning models into production. Architect scalable LLMOps pipelines on GCP / Vertex AI , including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop and deploy autonomous or semi-autonomous agents using modern agent frameworks and Google AI tooling. Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions. Monitor, optimise, and continuously improve models in live production environments. Contribute to the architecture and evolution of the AI platform and supporting data infrastructure. Stay current with emerging research, tools, and best practices across ML and Generative AI. What We're Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval-based architectures. Proven experience designing and operating large-scale ML systems in production . Strong experience with GCP Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with LLM evaluation frameworks such as RAGAS or TruLens . Experience fine-tuning large models or working with reinforcement learning techniques. Background in mathematics, statistics, or theoretical computer science. Understanding of data governance, bias mitigation, or model interpretability. Why Join Work on real, production-grade GenAI systems with clear business impact. High autonomy and ownership in a senior, hands-on engineering role. Fully remote working with a collaborative, distributed team. Opportunity to influence architecture and long-term technical direction. Competitive salary up to 100k , plus benefits.
AI UX Engineer - 350PD - Remote Required Technical Skills AWS & Generative AI Experience with AWS Bedrock including model selection, deployment, and prompt engineering Agentic workflow development, ideally using AWS AgentCore Multi-agent orchestration frameworks such as AWS Strands Agents, LangGraph, or similar LLM integration and fine-tuning (Claude, GPT-4, or equivalent) Strong prompt engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar Embedding model optimisation and semantic search Context window management and chunking strategies MCP & Tool Integration Model Context Protocol (MCP) implementation LLM tool calling and API design AWS Lambda integration with agents AI Safety & Evaluation Guardrail implementation (hallucination detection, toxicity filtering) Response evaluation frameworks and A/B testing Definition of AI performance metrics (accuracy, latency, user satisfaction) Programming & Development Advanced Python AWS SDK (boto3) Infrastructure as Code awareness (CloudFormation/Terraform) Git and CI/CD for ML systems UX Engineer - Skills & Requirements Design & Prototyping Advanced Figma skills Wireframing, interactive prototyping, and design systems Responsive web and mobile design Conversational UX Chatbot and conversational interface design Multi-turn conversation flows and context management Error handling and recovery patterns Frontend Development HTML, CSS, JavaScript/TypeScript React, Vue, or Angular Component-based architecture and state management API integration and async data handling AWS & Integration Basic AWS services (S3, CloudFront, API Gateway) Authentication (SSO, OAuth) WebSockets for real-time chat To apply for this role please submit your CV or contact Dillon Blackburn on (phone number removed) or at (url removed). Tenth Revolution Group are the go-to recruiter for Data & AI roles in the UK offering more opportunities across the country than any other recruitment agency. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, and the London Fabric User Group. We are the global leaders in Data & AI recruitment.
Dec 16, 2025
Contractor
AI UX Engineer - 350PD - Remote Required Technical Skills AWS & Generative AI Experience with AWS Bedrock including model selection, deployment, and prompt engineering Agentic workflow development, ideally using AWS AgentCore Multi-agent orchestration frameworks such as AWS Strands Agents, LangGraph, or similar LLM integration and fine-tuning (Claude, GPT-4, or equivalent) Strong prompt engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar Embedding model optimisation and semantic search Context window management and chunking strategies MCP & Tool Integration Model Context Protocol (MCP) implementation LLM tool calling and API design AWS Lambda integration with agents AI Safety & Evaluation Guardrail implementation (hallucination detection, toxicity filtering) Response evaluation frameworks and A/B testing Definition of AI performance metrics (accuracy, latency, user satisfaction) Programming & Development Advanced Python AWS SDK (boto3) Infrastructure as Code awareness (CloudFormation/Terraform) Git and CI/CD for ML systems UX Engineer - Skills & Requirements Design & Prototyping Advanced Figma skills Wireframing, interactive prototyping, and design systems Responsive web and mobile design Conversational UX Chatbot and conversational interface design Multi-turn conversation flows and context management Error handling and recovery patterns Frontend Development HTML, CSS, JavaScript/TypeScript React, Vue, or Angular Component-based architecture and state management API integration and async data handling AWS & Integration Basic AWS services (S3, CloudFront, API Gateway) Authentication (SSO, OAuth) WebSockets for real-time chat To apply for this role please submit your CV or contact Dillon Blackburn on (phone number removed) or at (url removed). Tenth Revolution Group are the go-to recruiter for Data & AI roles in the UK offering more opportunities across the country than any other recruitment agency. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, and the London Fabric User Group. We are the global leaders in Data & AI recruitment.
Decision Intelligence - Palantir Foundry, Lead Consultant, Senior Manager We are looking for a Senior Manager with deep Palantir Foundry expertise to lead the design and delivery of production-grade data and AI solutions. You will shape end-to-end architectures, lead multidisciplinary teams and work directly with senior client stakeholders to turn complex data, AI and process challenges into scalable Foundry applications. Key responsibilities Act as lead architect for Foundry, owning solution design from ingestion and pipelines through Ontology, applications and AI use cases. Translate business problems into Foundry use cases, technical designs and deliverable roadmaps. Design and oversee data pipelines, Ontology models, security and governance patterns and application workflows in Foundry. Guide teams of data engineers, software engineers and data scientists to deliver robust, secure and maintainable Foundry solutions. Integrate Foundry with wider enterprise platforms, cloud environments and downstream analytics tools. Build trusted relationships with senior stakeholders, shaping new opportunities and ensuring value realisation from the platform. Skills and experience Significant hands-on experience delivering Palantir Foundry solutions in complex client environments. Deep Foundry technical expertise across the full stack: Pipeline Builder, Ontology, Workshop, OSDK, Code Repositories, Actions and AIP or agentic capabilities, able to build production-grade applications not just prototypes. Strong proficiency in at least one relevant programming language such as Python or PySpark, Java, Typescript or SQL. Solid understanding of data engineering, data modelling, security and governance in enterprise settings. Experience with software engineering best practices including Git-based development, testing and CI or CD. Excellent communication and stakeholder management skills, with the ability to influence and align diverse technical and business audiences. Proven leadership in building, coaching and motivating technical teams. Sector experience in Financial Services, Government, Healthcare, Energy or Manufacturing is desirable. Eligibility for, or current possession of, government security clearance is an advantage. What you will receive You will join a specialist Foundry community, working on high-impact programmes with strong support for ongoing learning and certification. A competitive package typically includes flexible and hybrid working, health and wellbeing benefits, professional development support and paid volunteering or community days.
Dec 16, 2025
Decision Intelligence - Palantir Foundry, Lead Consultant, Senior Manager We are looking for a Senior Manager with deep Palantir Foundry expertise to lead the design and delivery of production-grade data and AI solutions. You will shape end-to-end architectures, lead multidisciplinary teams and work directly with senior client stakeholders to turn complex data, AI and process challenges into scalable Foundry applications. Key responsibilities Act as lead architect for Foundry, owning solution design from ingestion and pipelines through Ontology, applications and AI use cases. Translate business problems into Foundry use cases, technical designs and deliverable roadmaps. Design and oversee data pipelines, Ontology models, security and governance patterns and application workflows in Foundry. Guide teams of data engineers, software engineers and data scientists to deliver robust, secure and maintainable Foundry solutions. Integrate Foundry with wider enterprise platforms, cloud environments and downstream analytics tools. Build trusted relationships with senior stakeholders, shaping new opportunities and ensuring value realisation from the platform. Skills and experience Significant hands-on experience delivering Palantir Foundry solutions in complex client environments. Deep Foundry technical expertise across the full stack: Pipeline Builder, Ontology, Workshop, OSDK, Code Repositories, Actions and AIP or agentic capabilities, able to build production-grade applications not just prototypes. Strong proficiency in at least one relevant programming language such as Python or PySpark, Java, Typescript or SQL. Solid understanding of data engineering, data modelling, security and governance in enterprise settings. Experience with software engineering best practices including Git-based development, testing and CI or CD. Excellent communication and stakeholder management skills, with the ability to influence and align diverse technical and business audiences. Proven leadership in building, coaching and motivating technical teams. Sector experience in Financial Services, Government, Healthcare, Energy or Manufacturing is desirable. Eligibility for, or current possession of, government security clearance is an advantage. What you will receive You will join a specialist Foundry community, working on high-impact programmes with strong support for ongoing learning and certification. A competitive package typically includes flexible and hybrid working, health and wellbeing benefits, professional development support and paid volunteering or community days.
Palantir Foundry Lead Consultant - Lead architect and hands-on technical owner for Palantir Foundry implementations. You will design and build production-grade data and application workflows on Foundry, own technical decisions end-to-end and work directly with senior stakeholders while mentoring engineering teams. Core Responsibilities Foundry Solution Architecture & Build Own end-to-end solution design across: Data integration (Pipeline Builder/code-based pipelines, connectors, incremental loads). Ontology modelling (object/relationship design, semantics, versioning). Application layer (Workshop, Code Repositories, OSDK/APIs, Actions, AIP/agentic workflows). Define and implement patterns for data modelling, transformation, and lineage tracking. Design permission models (RBAC/ABAC), object-level security and auditability. Implement CI/CD and environment promotion strategies for Foundry artefacts. Scalability, Reliability & Operations Lead performance tuning for large-scale production deployments (eg parallelisation, partitioning, caching, compute configuration). Design monitoring, alerting and observability for pipelines, applications and integrations. Handle incident response and root cause analysis for platform and application issues. Define and enforce non-functional requirements (SLA/SLOs, resilience, disaster recovery). Client-Facing Engineering & Stakeholder Management Run technical discovery with senior stakeholders to translate business needs into concrete Foundry use cases. Present architectures, trade-offs and risk assessments to both technical teams and C-suite. Provide technical guidance on integration with existing enterprise systems (data warehouses, message buses, APIs, identity providers). Enablement, Mentoring & Standards Design and deliver technical bootcamps, hands-on labs and enablement plans for engineers, analysts and power users. Mentor engineers on Foundry internals, best practices, and debugging strategies. Contribute to and enforce internal standards: code quality, naming conventions, testing strategies, pipeline/app design patterns. Required Experience Extensive experience working with Palantir , ideally as a Forward Deployed Engineer or equivalent implementation role. Multiple large-scale Foundry implementations in production , with direct ownership of: Solution architecture Deployment strategy Operational runbook and handover Demonstrable enterprise experience with: Performance bottlenecks at scale Complex permissioning/security models Schema and ontology evolution Integration failures and incident recovery Strong client-facing track record with senior stakeholders and C-suite , including technical steering sessions and design reviews. History of teaching, mentoring or training engineers or mixed-ability teams on Foundry (eg bootcamps, internal academies, onboarding programmes). Exposure to Palantir product teams and a deep understanding of: Platform limitations and edge cases Common failure modes Practical workarounds and design patterns to avoid them Technical Skills Strong practical knowledge of core Foundry components: Pipeline Builder, Ontology, Workshop, Code Repositories, OSDK, Actions, AIP/agentic features. Proficiency in at least one general-purpose programming language commonly used with Foundry (eg Python, Java, or similar) for transformations, services, and integrations. Solid background in data engineering concepts: batch/stream processing, data modelling, data quality, and governance. Experience integrating Foundry with enterprise identity (SSO, SAML/OIDC), APIs, and existing data platforms. Familiarity with modern software engineering practices: version control, code review, automated testing, CI/CD, infrastructure-as-code (where applicable). Profile Deep technical but pragmatic: optimises for correctness, reliability and maintainability under real-world constraints. Systems thinker: able to model complex domains and understand end-to-end data and control flows. Clear communicator: can move seamlessly between low-level detail and high-level architecture with different audiences. Enjoys debugging hard problems, documenting patterns, and building repeatable, reusable solutions. Staffworx are a UK based Talent & Recruiting Partner, supporting Digital Commerce, Software and Value Add Consulting sectors across the UK & EMEA.
Dec 15, 2025
Palantir Foundry Lead Consultant - Lead architect and hands-on technical owner for Palantir Foundry implementations. You will design and build production-grade data and application workflows on Foundry, own technical decisions end-to-end and work directly with senior stakeholders while mentoring engineering teams. Core Responsibilities Foundry Solution Architecture & Build Own end-to-end solution design across: Data integration (Pipeline Builder/code-based pipelines, connectors, incremental loads). Ontology modelling (object/relationship design, semantics, versioning). Application layer (Workshop, Code Repositories, OSDK/APIs, Actions, AIP/agentic workflows). Define and implement patterns for data modelling, transformation, and lineage tracking. Design permission models (RBAC/ABAC), object-level security and auditability. Implement CI/CD and environment promotion strategies for Foundry artefacts. Scalability, Reliability & Operations Lead performance tuning for large-scale production deployments (eg parallelisation, partitioning, caching, compute configuration). Design monitoring, alerting and observability for pipelines, applications and integrations. Handle incident response and root cause analysis for platform and application issues. Define and enforce non-functional requirements (SLA/SLOs, resilience, disaster recovery). Client-Facing Engineering & Stakeholder Management Run technical discovery with senior stakeholders to translate business needs into concrete Foundry use cases. Present architectures, trade-offs and risk assessments to both technical teams and C-suite. Provide technical guidance on integration with existing enterprise systems (data warehouses, message buses, APIs, identity providers). Enablement, Mentoring & Standards Design and deliver technical bootcamps, hands-on labs and enablement plans for engineers, analysts and power users. Mentor engineers on Foundry internals, best practices, and debugging strategies. Contribute to and enforce internal standards: code quality, naming conventions, testing strategies, pipeline/app design patterns. Required Experience Extensive experience working with Palantir , ideally as a Forward Deployed Engineer or equivalent implementation role. Multiple large-scale Foundry implementations in production , with direct ownership of: Solution architecture Deployment strategy Operational runbook and handover Demonstrable enterprise experience with: Performance bottlenecks at scale Complex permissioning/security models Schema and ontology evolution Integration failures and incident recovery Strong client-facing track record with senior stakeholders and C-suite , including technical steering sessions and design reviews. History of teaching, mentoring or training engineers or mixed-ability teams on Foundry (eg bootcamps, internal academies, onboarding programmes). Exposure to Palantir product teams and a deep understanding of: Platform limitations and edge cases Common failure modes Practical workarounds and design patterns to avoid them Technical Skills Strong practical knowledge of core Foundry components: Pipeline Builder, Ontology, Workshop, Code Repositories, OSDK, Actions, AIP/agentic features. Proficiency in at least one general-purpose programming language commonly used with Foundry (eg Python, Java, or similar) for transformations, services, and integrations. Solid background in data engineering concepts: batch/stream processing, data modelling, data quality, and governance. Experience integrating Foundry with enterprise identity (SSO, SAML/OIDC), APIs, and existing data platforms. Familiarity with modern software engineering practices: version control, code review, automated testing, CI/CD, infrastructure-as-code (where applicable). Profile Deep technical but pragmatic: optimises for correctness, reliability and maintainability under real-world constraints. Systems thinker: able to model complex domains and understand end-to-end data and control flows. Clear communicator: can move seamlessly between low-level detail and high-level architecture with different audiences. Enjoys debugging hard problems, documenting patterns, and building repeatable, reusable solutions. Staffworx are a UK based Talent & Recruiting Partner, supporting Digital Commerce, Software and Value Add Consulting sectors across the UK & EMEA.
Job Title: AI Graph Enineer (Senior) Positions Available: x2 Salary: High rates on offer, contact for details - Initial daily pay rate for contract period before converting to salary Location: Abingdon, outside London Hours: Full time Monday to Friday Hyrbid: Hybrid working with 2-3 office days in Abingdon - fully remote may be an option for the right candidate Contract: FULL TIME initial 6 month contract, they are treating this as a â probation' type period, and if all goes well in the first 3-6 months then they will transition you into a permanent staff position or extend the contract if preferred Key Experience Requried: someone that has experience defining and buildig semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data. About the Role We are seeking a highly skilled AI Agent Engineer with deep experience in LangGraph, agentic AI workflows, ontology-driven knowledge graphs, and data systems integration. This role will focus on designing and building agentic workflows that enable natural-language querying across structured and unstructured data to deliver intelligent insights for analytics and decision-making. Candidate will architect and implement multi-step AI agents, integrate them with enterprise data platforms, and build semantic layers that support reasoning, retrieval, planning, and autonomous task execution across heterogeneous data sources. Experience in Oil & Gas data domains such as drilling, production, subsurface, HSE, or asset operations is highly preferred. Key Responsibilities Knowledge Graph & Ontology Engineering Define and build semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data. Architect and maintain knowledge graphs that integrate with enterprise data sources. Implement embeddings-assisted retrieval, RAG pipelines, and cross-domain entity linking. AI Agent & Workflow Development Design, build, and scale LangGraph-based agentic workflows for natural-language data exploration, insights generation, and analytics automation. Implement autonomous workflows including planning, retrieval, reasoning, and tool execution. Build modular, stateful agents capable of multi-step reasoning, context retention, and complex decision flows. Data Systems Integration Connect AI agents with relational databases (PostgreSQL, SQL Server, Oracle), graph databases (Neo4j, Neptune), and data lakes (S3, ADLS, Delta Lake). Build pipelines to ingest, index, and query both structured and unstructured data. Develop semantic query layers for NL-to-SQL, NL-to-GraphQL, or NL-to-SPARQL translations. Application & API Development Build Python services, APIs, and microservices for agent orchestration and data access. Collaborate with data engineering, analytics, and domain experts to deploy scalable solutions. Oil & Gas Domain Expertise Understand industry data models such as drilling logs, production data, wellbore schemas, seismic metadata, engineering documents, and operations workflows. Translate industry use cases into agentic AI workflows that deliver actionable insights. Required Skills & Experience Core Technical Skills LangGraph for agent orchestration (planning, memory, tools, multi-agent workflows). Python (advanced proficiency). Knowledge Graphs: building ontologies, semantic models, RDF/OWL, SPARQL. Graph Databases: Neo4j, Neptune or similar. Relational Databases: PostgreSQL, SQL Server, MySQL, Oracle; query optimization. Data Lakes: S3, ADLS, Delta Lake, Parquet/Arrow. RAG / Vector Databases: Postgres, Pinecone, Weaviate, Qdrant, Chroma or equivalent. Natural Language Query Systems: NL-to-SQL, semantic query engines, embedding models. AI/ML Skills Experience with LLM-based systems, prompt engineering, and structured agent design. Knowledge of retrieval strategies, hybrid search, and memory architectures. Familiarity with OpenAI, Azure OpenAI, Anthropic, or similar model providers. Architecture & Engineering Skills Microservices architecture, API development, containerization (Docker/Kubernetes). CI/CD and production ML/AI deployment best practices. Industry Skills Oil & Gas data models and standards (PPDM, WITSML, PRODML, RESQML preferred). Understanding of drilling operations, production operations, subsurface data, or engineering documents. Preferred Qualifications 6-10+ years of experience in data engineering, AI engineering, or knowledge graph engineering. 1+ years hands-on experience with LangChain/LangGraph or agentic AI frameworks. Experience designing enterprise-scale semantic or knowledge-centric systems. Prior experience implementing NLQ (natural language query) for analytics or BI. Experience in Oil & Gas digital transformation projects. Soft Skills Excellent problem-solving and conceptual modeling skills. Ability to work cross-functionally with data engineering, cloud teams, and business SMEs. Strong communication and technical documentation skills. Ability to translate ambiguous business requirements into technical workflows. With over 90 years' combined experience, NES Fircroft (NES) is proud to be the world's leading engineering staffing provider spanning the Oil & Gas, Power & Renewables, Chemicals, Construction & Infrastructure, Life Sciences, Mining and Manufacturing sectors worldwide. With more than 80 offices in 45 countries, we are able to provide our clients with the engineering and technical expertise they need, wherever and whenever it is needed. We offer contractors far more than a traditional recruitment service, supporting with everything from securing visas and work permits, to providing market-leading benefits packages and accommodation, ensuring they are safely and compliantly able to support our clients.
Dec 15, 2025
Full time
Job Title: AI Graph Enineer (Senior) Positions Available: x2 Salary: High rates on offer, contact for details - Initial daily pay rate for contract period before converting to salary Location: Abingdon, outside London Hours: Full time Monday to Friday Hyrbid: Hybrid working with 2-3 office days in Abingdon - fully remote may be an option for the right candidate Contract: FULL TIME initial 6 month contract, they are treating this as a â probation' type period, and if all goes well in the first 3-6 months then they will transition you into a permanent staff position or extend the contract if preferred Key Experience Requried: someone that has experience defining and buildig semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data. About the Role We are seeking a highly skilled AI Agent Engineer with deep experience in LangGraph, agentic AI workflows, ontology-driven knowledge graphs, and data systems integration. This role will focus on designing and building agentic workflows that enable natural-language querying across structured and unstructured data to deliver intelligent insights for analytics and decision-making. Candidate will architect and implement multi-step AI agents, integrate them with enterprise data platforms, and build semantic layers that support reasoning, retrieval, planning, and autonomous task execution across heterogeneous data sources. Experience in Oil & Gas data domains such as drilling, production, subsurface, HSE, or asset operations is highly preferred. Key Responsibilities Knowledge Graph & Ontology Engineering Define and build semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data. Architect and maintain knowledge graphs that integrate with enterprise data sources. Implement embeddings-assisted retrieval, RAG pipelines, and cross-domain entity linking. AI Agent & Workflow Development Design, build, and scale LangGraph-based agentic workflows for natural-language data exploration, insights generation, and analytics automation. Implement autonomous workflows including planning, retrieval, reasoning, and tool execution. Build modular, stateful agents capable of multi-step reasoning, context retention, and complex decision flows. Data Systems Integration Connect AI agents with relational databases (PostgreSQL, SQL Server, Oracle), graph databases (Neo4j, Neptune), and data lakes (S3, ADLS, Delta Lake). Build pipelines to ingest, index, and query both structured and unstructured data. Develop semantic query layers for NL-to-SQL, NL-to-GraphQL, or NL-to-SPARQL translations. Application & API Development Build Python services, APIs, and microservices for agent orchestration and data access. Collaborate with data engineering, analytics, and domain experts to deploy scalable solutions. Oil & Gas Domain Expertise Understand industry data models such as drilling logs, production data, wellbore schemas, seismic metadata, engineering documents, and operations workflows. Translate industry use cases into agentic AI workflows that deliver actionable insights. Required Skills & Experience Core Technical Skills LangGraph for agent orchestration (planning, memory, tools, multi-agent workflows). Python (advanced proficiency). Knowledge Graphs: building ontologies, semantic models, RDF/OWL, SPARQL. Graph Databases: Neo4j, Neptune or similar. Relational Databases: PostgreSQL, SQL Server, MySQL, Oracle; query optimization. Data Lakes: S3, ADLS, Delta Lake, Parquet/Arrow. RAG / Vector Databases: Postgres, Pinecone, Weaviate, Qdrant, Chroma or equivalent. Natural Language Query Systems: NL-to-SQL, semantic query engines, embedding models. AI/ML Skills Experience with LLM-based systems, prompt engineering, and structured agent design. Knowledge of retrieval strategies, hybrid search, and memory architectures. Familiarity with OpenAI, Azure OpenAI, Anthropic, or similar model providers. Architecture & Engineering Skills Microservices architecture, API development, containerization (Docker/Kubernetes). CI/CD and production ML/AI deployment best practices. Industry Skills Oil & Gas data models and standards (PPDM, WITSML, PRODML, RESQML preferred). Understanding of drilling operations, production operations, subsurface data, or engineering documents. Preferred Qualifications 6-10+ years of experience in data engineering, AI engineering, or knowledge graph engineering. 1+ years hands-on experience with LangChain/LangGraph or agentic AI frameworks. Experience designing enterprise-scale semantic or knowledge-centric systems. Prior experience implementing NLQ (natural language query) for analytics or BI. Experience in Oil & Gas digital transformation projects. Soft Skills Excellent problem-solving and conceptual modeling skills. Ability to work cross-functionally with data engineering, cloud teams, and business SMEs. Strong communication and technical documentation skills. Ability to translate ambiguous business requirements into technical workflows. With over 90 years' combined experience, NES Fircroft (NES) is proud to be the world's leading engineering staffing provider spanning the Oil & Gas, Power & Renewables, Chemicals, Construction & Infrastructure, Life Sciences, Mining and Manufacturing sectors worldwide. With more than 80 offices in 45 countries, we are able to provide our clients with the engineering and technical expertise they need, wherever and whenever it is needed. We offer contractors far more than a traditional recruitment service, supporting with everything from securing visas and work permits, to providing market-leading benefits packages and accommodation, ensuring they are safely and compliantly able to support our clients.
