61 jobs found

We are partnering with an established technology firm building high-scale software platforms for complex business applications. They are expanding their London team and looking for a Full Stack Software Engineer to join their team. If you enjoy end-to-end software delivery, from scalable Python backends and event-driven data pipelines to clean, modern frontends, this is a great opportunity to own product development. The Opportunity Salary: Up to £65,000 Location: Central London (5 Days Onsite) Type: Full-time, Permanent What You'll Be Building Architect production-grade Python services (FastAPI/Flask) within an event-driven architecture. Build relational models in Postgres, vector search, and streaming queues (Kafka/SNS/SQS). Craft responsive interfaces and dashboards in React or Vue.js. Deploy containerised applications (Docker) on AWS using Terraform. Build practical, production-ready interfaces for LLMs, RAG pipelines, and model endpoints into core products. What They're Looking For Strong foundation in Python, REST APIs, microservices, and clean code principles. Practical experience with React or Vue.js. Solid Postgres/SQL, AWS, and Docker experience (NoSQL/Terraform a plus). Exposure to LLMs, RAG, or ML model integration as part of a broader engineering stack. Must have unrestricted UK Right to Work.

AI/ML Engineer (SC Cleared) Salary: Up to £85,000 + Benefits Locations: Bristol, Cheadle (Stockport), Glasgow, Reading or Crawley Working Pattern: Hybrid Security Clearance: Active SC Clearance Required Akkodis is currently recruiting for two experienced AI/ML Engineers to design, develop and deploy secure AI solutions for autonomous and mission-critical systems. The Role You will work across the full AI life cycle from concept through deployment, helping deliver high-value AI programmes within defence and other safety-critical environments. Key Responsibilities . Design, develop and deploy AI and ML solutions. . Build machine learning, deep learning and computer vision models. . Develop solutions using LLMs and emerging AI technologies. . Support autonomous capabilities using ROS 2 and similar frameworks. . Implement robust software engineering, testing, CI/CD and MLOps practices. . Support bids, demonstrations, workshops and customer engagements. . Ensure adherence to Responsible AI, cyber security and safety standards. Essential Experience . Experience delivering AI and ML solutions in complex, safety-critical environments. . Strong Python development experience. . Expertise in Machine Learning, Deep Learning, Computer Vision and LLMs. . Experience with autonomous technologies and ROS 2. . Experience taking solutions from concept to deployment. . Knowledge of CI/CD, cloud technologies and MLOps. . Excellent stakeholder communication skills. Why Apply? . Salary up to £85,000. . Hybrid working across multiple UK locations. . Work on nationally significant programmes. . Career development within a world-leading technology organisation. Modis International Ltd acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers in the UK. Modis Europe Ltd provide a variety of international solutions that connect clients to the best talent in the world. For all positions based in Switzerland, Modis Europe Ltd works with its licensed Swiss partner Accurity GmbH to ensure that candidate applications are handled in accordance with Swiss law. Both Modis International Ltd and Modis Europe Ltd are Equal Opportunities Employers. By applying for this role your details will be submitted to Modis International Ltd and/or Modis Europe Ltd. Our Candidate Privacy Information Statement which explains how we will use your information is available on the Modis website.

The Role This is a senior, forward-deployed analytics leadership role - responsible for taking analytics and AI capabilities out of development and into the commercial reality of Chubb's EMEA insurance business. This role is not a central analytics function. It is a deployment-first role, embedded at the intersection of data science, engineering, and business - where the measure of success is analytics operating reliably in production, driving measurable commercial outcomes. The Analytics Solution Lead owns the full journey from analytical development to business adoption: designing production-ready solutions, driving deployment into operational systems, and embedding analytics into how underwriters, pricing teams, and portfolio managers actually make decisions. You will bring field learnings back to sharpen the analytics roadmap, proactively identify new deployment opportunities across the business, and lead the cultural shift that turns analytical output into operational capability. It is a delivery and adoption role - combining the technical credibility to work alongside AI engineers, data scientists and architects, the business fluency to engage senior underwriting ,pricing and Ops leaders, and the deployment mindset to get things done in complex, regulated environments. Core Responsibilities Embed directly with business stakeholders - underwriters, pricing leads, portfolio managers - to understand how analytics can change how they make decisions, not just what information they have Deploy solutions rapidly and iteratively: ship working capability quickly, gather real-world feedback, and improve - consistent with a field-first deployment philosophy Drive adoption of deployed analytics: ensure tools and models are being used, understood, and trusted by the people they were built for Define solution specifications and deployment requirements that enable Solution Architects and Deployment Engineers to build and release production-grade analytics solutions Collaborate with Solution Architects to ensure analytics designs conform to enterprise architecture standards, platform constraints, and non-functional requirements (scalability, security, latency, auditability) Define measurable success criteria for every deployed solution - not just technical metrics, but commercial outcomes (e.g. pricing accuracy, hit rate improvement, loss ratio movement, underwriter decision quality) Design and lead change management plans for analytics deployment - ensuring that new tools and models are adopted, not just installed Develop and deliver targeted enablement for business users: from underwriter training on model outputs to pricing team workflows that embed decision support Qualifications Required Experience 8+ years in data science, analytics, analytics engineering, or forward-deployed analytics/AI roles - with a demonstrable track record of getting analytics into production in complex organisations Proven experience deploying analytics solutions end-to-end - from problem framing through to production, adoption, and impact measurement Experience embedding directly with business stakeholders and driving behavioral change through analytics - not just delivering technical outputs Demonstrated ability to measure and communicate the commercial impact of analytics deployments Experience working across analytics and engineering teams - translating model outputs and analytical designs into deployment-ready specifications Ability to engage credibly with Solution Architects on design trade-offs, platform constraints, and integration patterns Experience designing and operating model monitoring frameworks - drift detection, performance tracking, alerting Experience defining solution governance frameworks - handoff documentation, acceptance criteria, deployment standards Exposure to GenAI / LLM deployment in enterprise settings Cloud platform experience - Azure preferred Experience working in regulated industries - insurance or financial services strongly preferred Demonstrable experience with responsible AI practices - explainability, bias review, model auditability Desirable Experience with insurance platforms (Duck Creek, Guidewire, Acturis) Experience with pricing or actuarial model deployment Familiarity with MLOps concepts (CI/CD pipelines, model registries, automated testing) - awareness required, not hands-on ownership Experience with ML lifecycle tooling - MLflow, Azure ML, or equivalent Python proficiency - able to read and review analytical code, contribute where needed Consulting or forward-deployed engineering background (Palantir, QuantumBlack, or equivalent) Experience leading or mentoring data scientists and analytics professionals We offer in return! Competitive salary & pension scheme Discretionary bonus scheme 25 days annual leave plus ability to purchase 5 additional days Hybrid working options Private Medical cover Employee Share Purchase Plan Life Assurance Subsidised gym membership Comprehensive Learning & development offerings Employee Assistance program Integrity. client focus. respect. excellence. teamwork Our core values dictate how we live and work. We're an ethical and honest company that's wholly committed to its clients. A business that's engaged in mutual trust and respect for its employees and partners. A place where colleagues perform at the highest levels. And a working environment that's collaborative and supportive. Diversity & Inclusion. At Chubb, we consider our people our chief competitive advantage and as such we treat colleagues, candidates, clients, and business partners with equality, fairness and respect, regardless of their age, disability, race, religion or belief, gender, sexual orientation, marital status or family circumstances. We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or long-term condition (for example dyslexia, anxiety, autism, a mobility condition or hearing loss) and need us to make any reasonable adjustments, changes or do anything differently during the recruitment process, please let us know.

Backend Software Engineer / Developer (Python LLM MLOps) London / WFH to £90k Are you an experienced Backend Software Engineer with strong Python skills and a good knowledge of AI, LLMs and agentic coding? You could be progressing your career at a global finance technology consultancy, working with clients including global Investment Banks and financial services organisations. What's in it for you: Salary to £90k Pension, Life Assurance, Income Protection Private medical care for you and your family, including mental health Travel Insurance Charitable giving Gym membership for you and your family Flexible holiday scheme Your role: As a Backend Software Engineer you'll design and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video), design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments. Using a consultative approach you'll guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption. About you: You have achieved a 2.1 or above bachelor's degree in Computer Science, AI or related STEM disciplines You have a strong Python software engineering background including and API development You have hands-on experience deploying LLMs and multi-modal models at scale in production You have a strong understanding of scalable MLOps, observability and cloud-native AI deployment You're collaborative and pragmatic with advanced stakeholder communication, problem-solving and project management skills in Agile environments Experience with any of the following is advantageous: agentic frameworks (e.g., LangChain, LlamaIndex), deep learning frameworks, Langfuse, Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Backend Software Engineer / Developer (Python LLM MLOps RAG MCP) opportunity.

AI Engineer / Developer (Python LLM) London / WFH to £65k Want to work on intellectually and technically challenging AI systems at the cutting edge of what is possible, whilst learning and collaborating with an amazing team and enjoying flexible working and a range of other perks? You could be progressing your career as an AI Engineer at a well established AI company acting as tech incubator within the World Economic Forum to tackle issues like climate change, AI adoption, battery technology and other real world problems. As an AI Engineer you will develop backend code and APIs, with a focus on prompt engineering and LLMs, collaborating with the Technical Architect to develop robust and highly performant solutions. You'll build and deploy intelligent agents that can perform practical, commercially valuable tasks rather than simply experiment with AI models. The role will involve understanding how to get the best performance from tools such as Claude and ChatGPT, integrating them into robust workflows and turning them into usable products. You'll work alongside a talented team contributing ideas within a supportive and diverse team environment. Location / WFH: You'll be joining a friendly and supportive team in London with flexibility to work from home once a week. About you: You are a bright, proactive individual and a strong problem solver with commercial acumen You have strong Python software engineering skills, across the full development lifecycle through to testing and deployment You have experience building AI agents or automating business processes using agentic technology You have experience of working with and creating JSON based REST APIs You're keen to work in a start-up environment You have excellent communication and collaboration skills You are a passionate technologist, keep up to date with the latest innovations and learn new things You have solid knowledge of software engineering principles, Agile practices, CI/CD and ideally have experience within a cloud environment (AWS preferred) Experience of interfacing with database products / languages; Neo4J or other graph database would be ideal You are degree educated, having achieved a minimum 2.1 from a top tier university What's in it for you: As an AI Engineer, you will earn a competitive package including: Salary to £65k Bonus EMI share options Pension Healthcare Work with the latest cutting-edge AI technologies Excellent training and career development opportunities Apply now to find out more about this AI Engineer / Developer (Python LLM) role.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Code. Analyse. Transform. For those with a passion for data that can solve big challenges and reimagine finance, this is the opportunity for you. Duration - 2 years Salary - £48,500 plus fantastic benefits Locations - Bristol, Edinburgh, Leeds, Halifax, London and Manchester. You may need to have regional flexibility whilst on programme. Mix office and home working with our hybrid working policy. Qualifications - Choose from various qualifications to boost your career, including certifications through Stanford University Online. Work to a personal learning plan that matches your interests and goals. Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show. You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. Two years. Two game-changing rotations This two-year programme blends office and home working. Across two year-long placements, you'll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with some of the biggest datasets in the UK - using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Cloud-native AI engineering and large-scale data platforms , leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale. Advanced analytics, statistical learning and decision intelligence , applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems , building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance , designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives. Responsible AI, explainability and algorithmic governance , applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities. Your skills toolkit You'll master: Python & SQL Cloud platforms like GCP Data Analysis Machine learning techniques, both theory and application Generative and Agentic AI AI Solution design and evaluation techniques CI/CD and DevOps all delivered through a commercial lens Your multi-week AI power-up We start with a blended learning bootcamp. Your fast track from fundamental concepts to advanced technologies and AI skills (and your chance to learn a few tricks even the bots don't know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects to build your network, test fresh ideas and put your creativity to work. The team in your corner A dedicated mentor A close-knit community of data professional who speak fluent Python and coffee, naturally Your future. Fully funded You'll earn a good salary while mastering the skills shaping the future of tech and finance. Training? Bootcamp? Certifications? All on us. By the end, you'll have the technical confidence, strategic mindset and industry know-how to take your career wherever you want - from deep technical roles to AI strategy leadership or even inventing the next big thing that no-one has thought of yet. Requirements What you need to apply While we do not require a set minimum degree achievement, we strongly recommend the ability to be able to demonstrate sound knowledge, understanding and technical skills aligned to the role. Some aspects of this will be assessed through the application process. We encourage all students to apply, from newly graduated through to MSc/PhD. Note: we cannot sponsor visas. Knowledge of analytical techniques and experience in manipulating and deriving insight from data. Python coding experience, knowledge of SQL and the ability to use statistical modelling techniques as this will form a part of the assessments. Locations Bristol, Edinburgh, Halifax, Leeds, London, Manchester. You will be expected to work in your allocated office a minimum of two days a week as part of our hybrid working policy. Opening and Closing Date Applications for our Data Science & AI Graduate Scheme opens on 10 th September and close on the 29 th November, except for the London location which closes on 11th October. Apply soon as our programmes may close early if we receive a high number of applications. How to Apply Our application process is designed to help you shine. We want everyone to feel they belong and can be their best, regardless of background, identity, or culture. Find details, including stages and tips for success, on our How to Apply page.

Lead AI Labs Software Engineer (Programmer Software Engineer Developer Python Amazon Web Services AWS Strands Agents AI LangChain LangGraph CrewAI Google AutoGen Pydantic AI PydanticAI Bedrock AgentCore ADK Azure GCP Cloud Asset Manager Buy Side Investment Management Fund Hedge Fund Finance Financial Services Banking Front Office Trading Asset Manager) required by our client in finance in London. You MUST have the following: Advanced experience as a Python Software Engineer/Programmer/Developer Leadership experience for the delivery of projects from beginning to end- inception to production Excellent interpersonal skills Advanced design and architecture ability Creating Agentic AI solutions, collaborating with business stakeholders to understand their needs The following is DESIRABLE, not essential: Experience taking Agentic AI solutions into production AWS AWS Strands Agents, LLM, Pydantic AI, Bedrock, AgentCore, ADK, CrewAI, AutoGen LangChain and LangGraph Finance Role: Lead AI Labs Software Engineer (Programmer Software Engineer Developer Python Amazon Web Services AWS Strands Agents AI LangChain LangGraph CrewAI Google AutoGen Pydantic AI Bedrock AgentCore ADK Azure GCP Cloud Asset Manager Buy Side Investment Management Fund Hedge Fund Finance Financial Services Banking Front Office Trading Asset Manager) required by our client in finance in London. You will be a lead engineer, working with a manager and two seniors to run the AI labs for the company's UK office. The company has an existing list of UK requirements from its investment, sales and marketing departments that need to be fulfilled with Agentic AI solutions. In the next 6 months, the team is expected to grow out further with another lead and two more seniors, distributing the departments between the teams. You will have experience in building Agentic AI solutions and taking them to production. In the role, you will be working with AWS, AWS Strands Agents, LangChain and LangGraph, although you do not need experience of these particular tools. Nor do you need experience in finance. The timeframes for delivering these solutions in the role will be about 3 months at a time. Once in production, the solutions will be transferred to the departmental tech teams. As many of the company's clients are going through their own AI journeys, from time to time, you will also showcase the team's solutions to clients. This may also lead to some partnerships with clients to build solutions. Your background will be as a Python Developer. The interview process will include a Python pair-programming round and an architectural interview. Hybrid working is 3 days/week in the office. Hours are 9am-5pm. Salary: £150k - £180k + 25% Bonus + 10% Pension

Lead AI Architect Permanent Various Locations SC Clearance preferred We're seeking a Lead AI Architect to drive the delivery of large scale AI and Data transformation programmes within the Security & Justice sector. This is a hands on leadership role focused on taking AI solutions from proof of concept through to secure, scalable, production-grade deployments in highly regulated environments. The successful candidate will combine deep technical expertise in AI/ML, LLMs, Generative AI and cloud platforms with strong delivery leadership and stakeholder engagement skills. They will be responsible for designing end-to-end AI architectures, leading multidisciplinary teams, shaping technical roadmaps, and ensuring solutions meet stringent security, governance and operational requirements. Key Experience Required Proven track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms (Azure, AWS or GCP) Experience deploying AI solutions within government, defence, healthcare or other high-assurance environments Strong understanding of AI security, governance, ethical AI, model evaluation and risk management Excellent stakeholder management skills with the ability to translate complex technical concepts into business value Ideal Candidate A hands on AI leader who has successfully delivered real-world AI systems at scale, balancing technical architecture, engineering excellence, client engagement and delivery leadership within complex, mission-critical environments. If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.

Lead AI Labs Software Engineer (Programmer Software Engineer Developer Python Amazon Web Services AWS Strands Agents AI LangChain LangGraph CrewAI Google AutoGen Pydantic AI Bedrock PydanticAI AgentCore ADK Azure GCP Cloud Asset Manager Buy Side Investment Management Fund Hedge Fund Finance Financial Services Banking Front Office Trading Asset Manager) required by our client in finance in London. You MUST have the following: Advanced experience as a Python Software Engineer/Programmer/Developer Leadership experience for the delivery of projects from beginning to end- inception to production Excellent interpersonal skills Advanced design and architecture ability Creating Agentic AI solutions, collaborating with business stakeholders to understand their needs The following is DESIRABLE, not essential: Experience taking Agentic AI solutions into production AWS AWS Strands Agents, LLM, Pydantic AI, Bedrock, AgentCore, ADK, CrewAI, AutoGen LangChain and LangGraph Finance Role: Lead AI Labs Software Engineer (Programmer Software Engineer Developer Python Amazon Web Services AWS Strands Agents AI LangChain LangGraph CrewAI Google AutoGen Pydantic AI Bedrock AgentCore ADK Azure GCP Cloud Asset Manager Buy Side Investment Management Fund Hedge Fund Finance Financial Services Banking Front Office Trading Asset Manager) required by our client in finance in London. You will be a lead engineer, working with a manager and two seniors to run the AI labs for the company's UK office. The company has an existing list of UK requirements from its investment, sales and marketing departments that need to be fulfilled with Agentic AI solutions. In the next 6 months, the team is expected to grow out further with another lead and two more seniors, distributing the departments between the teams. You will have experience in building Agentic AI solutions and taking them to production. In the role, you will be working with AWS, AWS Strands Agents, LangChain and LangGraph, although you do not need experience of these particular tools. Nor do you need experience in finance. The timeframes for delivering these solutions in the role will be about 3 months at a time. Once in production, the solutions will be transferred to the departmental tech teams. As many of the company's clients are going through their own AI journeys, from time to time, you will also showcase the team's solutions to clients. This may also lead to some partnerships with clients to build solutions. Your background will be as a Python Developer. The interview process will include a Python pair-programming round and an architectural interview. Hybrid working is 3 days/week in the office. Hours are 9am-5pm. Salary: £120k - £150k + 25% Bonus + 10% Pension

Job title: Cyber AI Engineer - OpenAI / LLM / RAG Location: Remote Rate: 400 - 425 per day Contract: 6 months rolling Candidates must be willing and eligible to go through SC security clearance for this role. Want to work at the intersection of Generative AI and Cyber Security? We're looking for a Cyber AI Engineer to help turn cutting-edge AI capabilities into practical solutions for Security Operations Centres (SOCs). This is a hands-on role focused on prototyping, experimentation and proof-of-concept development - taking ideas from discovery through to working AI solutions that could genuinely augment cyber analysts and operations. You'll work closely with an AI Solution Architect and Business Analyst, translating cyber use cases into secure, measurable and technically viable AI solutions. Responsibilities: Designing and developing OpenAI-powered solutions for cyber security operations Building and integrating LLM, Generative AI and RAG solutions Developing AI assistants, copilots and agentic AI workflows Experimenting with multi-agent orchestration and knowledge retrieval Developing AI solutions using Python and modern AI frameworks Working with vector databases and retrieval technologies Integrating AI capabilities with SIEM, SOAR and wider cyber platforms Designing prompts and optimising LLM performance Building proofs-of-concept and technical prototypes Developing evaluation frameworks to test model performance, accuracy and reliability Applying Responsible AI and AI safety controls Ensuring solutions are built with security, scalability and operational requirements in mind Working with technical and non-technical stakeholders to turn ideas into workable solutions Required Expereince: We're interested in engineers who have genuine hands-on experience with Generative AI and LLM technologies, ideally alongside an understanding of cyber security operations. You'll ideally bring experience across: OpenAI platform / API development LLMs and Generative AI RAG implementation Prompt engineering and optimisation AI assistants / copilots Agentic AI or multi-agent systems Python development Vector databases and knowledge retrieval AI evaluation and model testing API integration and secure software engineering Cyber Security / SOC environments SIEM / SOAR technologies Rapid prototyping and PoC development You don't need to have done everything above. Strong practical GenAI engineering experience combined with an interest in applying AI to cyber security is what matters. The opportunity This isn't a role where you'll simply be talking about what AI could do. You'll be building it, testing it and proving whether it works against real cyber security use cases. If you're an AI Engineer, GenAI Engineer, LLM Engineer or Python Engineer who wants to move deeper into Cyber AI, this is an opportunity to work on some genuinely interesting problems across AI, automation and security operations.

Senior Full Stack Applied AI Engineer - Insurance - Permanent & competitive salary Our client, a leading London Market insurer, is looking for a Senior Full Stack Applied AI Engineer to join their Innovation team! This role is focused on taking AI ideas from concept through to working prototype, testing what actually works and helping successful solutions move into production. This is a genuinely hands-on role for someone who wants to build with the latest AI technology, rather than just talk about it. You'll be working across GenAI, agentic systems, Back End services, APIs, data and Back End development, with a strong focus on Google Cloud. You'll be a great fit if you have: Strong hands-on experience building GenAI/applied AI solutions, ideally within Google Cloud Experience with LLMs, AI agents and agent frameworks, ideally ADK, with knowledge of A2A/MCP Strong Python skills and full-stack development experience, particularly Back End, APIs and services Experience with RAG, Vector Search, model evaluation and modern AI application development A strong software engineering background with experience across cloud, databases, Docker/Kubernetes, CI/CD and Terraform The role requires 3-4 days pw in London and is paying between £130,000 - £175,000pa with bonus and benefits on top. The processing and use by us of your personal data is in accordance with our Privacy Notice which can be found on our website. We know that the most successful teams have a diversity of background, experience and approach. When we recruit, we welcome the unique contributions you can bring thanks to your sex, ethnicity, race, gender identity, nationality, age, disability and beliefs. Senior Full Stack Applied AI Engineer - Insurance - Permanent & competitive salary

Full Stack Engineer Contract 6 months+ UK hybrid Active SC required Morela is proud to be supporting a sovereign AI business whose software has to run where most software cannot: offline, locked down, and under real scrutiny. Their platform is an AI operating system built for exactly those conditions. They are well funded, growing quickly, and already live on serious government and commercial programmes. The engineering team is small and senior, so nobody here is a spare pair of hands. The Job You would sit inside the delivery team on a defence programme and build across the whole stack. Python services and pipelines at one end, the TypeScript front end that operators actually use at the other. The environments you ship into have no internet, the deadlines do not move, and the requirements will. It is a high trust seat. You take a problem from a conversation with the customer through to something running in production, and you are the one on site when it needs fixing. In exchange you get properly hard problems, senior people around you, and real influence over a product that matters. Not many engineers get this close to sovereign AI in defence. What is being built here will shape how these organisations work for years. What the Work Looks Like Building and maintaining features top to bottom: Python back end services and APIs, React and TypeScript on the front. Getting software into secure, air-gapped and sensitive environments, which means on-site deployment, integration and troubleshooting. Owning features properly. Scope it with the technical lead, CTO and customer, build it, test it, ship it, then support it. Containerising services and shaping how the platform runs on Kubernetes and bare-metal Linux. Writing code you would be happy to inherit, and holding that same line in review. Fixing production problems calmly, usually with less tooling than you would like and someone waiting on you. Working alongside the data, AI and platform engineers so models, pipelines and infrastructure land as one product rather than three. Improving the day to day: CI/CD, observability, security hardening, documentation. Sitting in front of customers and partners and turning what they need into something buildable. What You Will Need Python. Serious commercial experience building back end services, APIs and tooling. FastAPI, Django, Flask, whichever you have used in anger. TypeScript. Serious commercial experience on modern front ends with React, Vue or Angular. Linux. Properly comfortable without a GUI: shell, networking, processes, permissions, systemd, packages, and working out why a host is misbehaving. Full stack delivery. A track record of shipping whole features from database to browser, relational databases and SQL included. Containers and CI/CD. Docker plus automated build, test and deploy pipelines. Composure. You have delivered against customer deadlines that do not slip, and you get methodical rather than frantic when something breaks. Secure environment fit. Happy following strict security and handling procedures, and getting to UK customer sites when the programme needs you there. Communication. Clear with engineers and with customers who are not engineers. Clearance. Current, active SC. You must be UK based and able to hold and maintain UK clearance. What Would Put You Ahead Delivery into defence, national security or another heavily regulated sector. Running software in air-gapped or disconnected environments, including offline dependencies and moving artefacts across the boundary. Good instincts on secure development, authentication, authorisation and secrets management. Putting AI or ML models into production, LLM features included. Infrastructure as code with Terraform, Ansible or similar, plus configuration management. Observability and incident response: metrics, logging, tracing. Message queues, event-driven architectures or data pipelines. Also Welcome Kubernetes. Deploying, running or debugging workloads, including K3s, RKE2 or OpenShift. Data at scale. Spark, Trino, Parquet, Iceberg or similar columnar and distributed query tooling. GPU workloads and serving models on-premise. Open source contributions or a portfolio worth a look. Mentoring engineers or leading a small delivery team. DV clearance, or eligibility for it. Interested? Get in touch with Morela for a confidential conversation.

AI Engineer Location : Woking, Surrey Salary : Up to £85,000 depending on experience The Opportunity We re working with an established and growing Managed Service Provider that is looking to bring an experienced AI Engineer into the business to help shape and deliver its AI capabilities. This is an exciting opportunity for someone who understands not just AI development, but how to implement practical AI solutions within a managed service environment and deliver genuine value to customers. You ll work closely with technical and commercial teams to identify opportunities for AI adoption, design and implement solutions, and help customers make effective use of emerging technologies. Key Responsibilities Design, develop and implement AI solutions for customers and internal business requirements Identify opportunities where AI, automation and machine learning can improve business processes Integrate AI technologies into existing IT environments and managed service solutions Work with Microsoft and cloud-based AI technologies, APIs and automation platforms Develop and deploy AI-powered tools, workflows and applications Support the implementation of Generative AI and Large Language Model (LLM) solutions Work with customers to understand their requirements and translate them into practical AI solutions Ensure AI implementations are secure, scalable and aligned with business objectives Troubleshoot and optimise AI solutions once deployed Keep up to date with emerging AI technologies and identify opportunities to introduce them into the wider service offering Provide technical guidance and knowledge sharing to colleagues across the business About You We re looking for an experienced AI professional who is comfortable working in a customer-facing Managed Service Provider environment. Ideally, you ll have: Proven experience working as an AI Engineer, AI Consultant, Machine Learning Engineer or similar Practical experience implementing AI solutions within an MSP or managed service environment Strong understanding of Generative AI, LLMs and AI automation Experience working with cloud platforms, APIs and AI services Knowledge of Microsoft technologies and the wider Microsoft ecosystem Experience integrating AI into existing systems and business processes Strong understanding of security, data protection and responsible AI implementation Excellent problem-solving and communication skills The ability to explain complex AI concepts to both technical and non-technical audiences A commercially minded approach, with an understanding of how AI can solve real-world customer problems Desirable Experience Experience with some of the following would be advantageous: Microsoft Azure / Azure AI Microsoft Copilot / Copilot Studio Azure OpenAI OpenAI APIs Python PowerShell Power Automate Machine Learning RAG (Retrieval-Augmented Generation) AI agents and automation API integrations Microsoft 365 Cybersecurity and AI governance What's on Offer? Salary up to £85,000 Hybrid working available for the right candidate Opportunity to play a key role in developing an MSP's AI offering Work across a variety of customer environments and projects Significant autonomy and ownership Opportunity to work with some of the latest AI technologies Career progression as the AI function continues to grow The client is looking to fill this opportunity immediately, so please apply ASAP or feel free to drop me an email with any questions to . com. SER-IN

AI Product Analyst (AI Metrics & Model Evaluation) London 80,000- 85,000 Join an award-winning, internationally recognised consultancy that's growing fast and building client-facing, cutting-edge AI products used across highly regulated industries, where real users act on high-level advice relating to legislative, regulatory and legal frameworks. As AI Product Analyst you'll play a key role in providing high-level insight into how much the AI products are being used, how well the AI models and agents are working, and reporting on the key analytics - segmenting the data to highlight trends by client, sector and question type. You will own the AI metrics and model evaluation capability that shapes the next stage of generative and agentic AI development. The role splits into two dynamic elements: AI metrics tell you how the product is performing in the hands of actual users, and model evaluation tells you whether a change is good enough to release. You'll report into the AI leadership team and work day to day with Product, Engineering and the in-house experts who know what a correct answer looks like. The scope will include; Defining the AI metrics that matter, retrieval quality, correctness of output, and what users go on to do with what they're given Owning production quality observability, from thumbs-down and regeneration rates through to abandoned tasks and drift in how the product is being used Building the analysis and dashboards the team works from, and specifying what needs capturing when the product itself has to change to get the AI metrics you need Digging into the data to work out what's really going on, the patterns, the outliers and the likely causes, then deciding which of it matters commercially Choosing the right method for the question, whether that's segmentation, cohort comparison, trend analysis or something built for the purpose, rather than reporting the same six metrics every month Owning the model evaluation programme: what gets tested, how much it covers, and what the results actually tell us Owning the golden datasets that underpin model evaluation, building them, extending them, versioning them and keeping them honest and running elicitation sessions with subject-matter experts to capture the professional judgement behind a right answer Turning findings into recommendations and following them through, so the insight changes something rather than sitting in a report Saying so clearly when model evaluation coverage isn't strong enough to call a release Essential Experience Solid experience as a product, data or commercial analyst, having owned measurement for a product or service end to end Strong hands-on SQL and Python, to the point where you build your own analysis and your own dashboards rather than queuing for someone else to do it The judgement to choose the right method for a question, and to know which lines of enquiry are worth your time Comfort working with the output of AI or machine-learning systems, and a clear view of why AI metrics and model evaluation differ from measuring a deterministic product A track record of getting knowledge out of experts and turning it into something structured and reusable The ability to put a recommendation in front of senior people and hold your position, particularly when they don't want to hear it Desirable experience Hands-on model evaluation with LLMs: golden datasets, scoring and regression testing. Retrieval-augmented systems and the AI metrics used to assess them Experiment design and A/B testing A regulated professional services environment This is a defining appointment for a fast-growing AI function, and a rare opportunity to build an AI metrics and model evaluation capability from first principles rather than inherit one. You will set the standards against which product quality is judged and release decisions are made, so your work determines what ships, not what gets reported afterwards. The role carries genuine autonomy, direct exposure to senior leadership, and the backing of an executive team with a clear AI roadmap. INDAMS The Portfolio Group are acting on behalf of our client in recruiting for this position.