Robson Bale Ltd
Senior AI Engineer - Permanent - London/Hybrid Permanent Hybrid in Central London Competitive Salary Key Responsibilities Technical Design & Delivery Contribute to the technical design and architecture of scalable AI solutions. Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements. Participate in technical design reviews and support architectural decisions for complex AI initiatives. Help implement responsible AI, model governance, and production machine learning practices. Work with technical and product stakeholders to translate business requirements into practical AI solutions. Provide technical insights and feasibility assessments to support product and engineering decisions. Technical Expertise & Execution Solve complex AI engineering challenges and provide technical guidance to other engineers. Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use. Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies. Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes. Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems. Engineering Standards & Enablement Contribute to engineering best practices, coding standards, and quality benchmarks for AI development. Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation. Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing. Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance. Promote maintainable, observable, secure, and well-tested approaches to AI engineering. Cross-functional Collaboration Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively. Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements. Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders. Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services. Skills, Knowledge and Expertise Must Have 5+ years of software engineering experience, including 2+ years building production AI, Generative AI, or RAG systems. Strong experience designing, building, deploying, and maintaining AI systems in production environments. Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact. Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques. Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation. Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code. Production experience with AWS cloud services and containerised environments, including Kubernetes. Experience building reliable APIs, services, and integration patterns for AI-enabled applications. Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition. Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation. Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams. Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation. Nice to Have Experience with model fine-tuning, RLHF, or custom training approaches. Familiarity with MLOps platforms and experiment-tracking tools. Experience with infrastructure as code, such as Terraform or CloudFormation. Experience with LLM evaluation, tracing, prompt management, or AI observability platforms. Background in NLP research or contributions to open-source AI or machine learning projects.
Senior AI Engineer - Permanent - London/Hybrid Permanent Hybrid in Central London Competitive Salary Key Responsibilities Technical Design & Delivery Contribute to the technical design and architecture of scalable AI solutions. Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements. Participate in technical design reviews and support architectural decisions for complex AI initiatives. Help implement responsible AI, model governance, and production machine learning practices. Work with technical and product stakeholders to translate business requirements into practical AI solutions. Provide technical insights and feasibility assessments to support product and engineering decisions. Technical Expertise & Execution Solve complex AI engineering challenges and provide technical guidance to other engineers. Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use. Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies. Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes. Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems. Engineering Standards & Enablement Contribute to engineering best practices, coding standards, and quality benchmarks for AI development. Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation. Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing. Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance. Promote maintainable, observable, secure, and well-tested approaches to AI engineering. Cross-functional Collaboration Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively. Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements. Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders. Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services. Skills, Knowledge and Expertise Must Have 5+ years of software engineering experience, including 2+ years building production AI, Generative AI, or RAG systems. Strong experience designing, building, deploying, and maintaining AI systems in production environments. Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact. Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques. Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation. Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code. Production experience with AWS cloud services and containerised environments, including Kubernetes. Experience building reliable APIs, services, and integration patterns for AI-enabled applications. Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition. Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation. Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams. Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation. Nice to Have Experience with model fine-tuning, RLHF, or custom training approaches. Familiarity with MLOps platforms and experiment-tracking tools. Experience with infrastructure as code, such as Terraform or CloudFormation. Experience with LLM evaluation, tracing, prompt management, or AI observability platforms. Background in NLP research or contributions to open-source AI or machine learning projects.
Adria Solutions Ltd
City, Manchester
Senior AI Engineer Manchester A growing technology-led business is seeking a Senior AI Engineer to play a pivotal role in shaping and delivering its AI strategy. This is a senior-level, hands-on position responsible for designing, building, and deploying enterprise-grade AI solutions that drive measurable business value across the organisation. Working closely with IT, Data, Engineering, and senior business stakeholders, you will lead the development and implementation of advanced AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Machine Learning, and Azure AI services. You will provide technical leadership, establish best practices, and help build the organisation s long-term AI capability. The business is investing heavily in AI and is looking for someone who can combine deep technical expertise with strategic thinking, taking solutions from concept through to production deployment and adoption. The ideal candidate will have a strong foundation in AI Engineering combined with a robust Data Science background, enabling them to develop, evaluate, and optimise AI solutions that deliver measurable business outcomes. This role would suit an experienced AI professional who enjoys solving complex business challenges, mentoring others, influencing technical direction, and delivering innovative AI solutions at scale. Role Purpose As a Senior AI Engineer, you will lead the design, development, deployment, and optimisation of enterprise AI solutions, ensuring they are secure, scalable, maintainable, and aligned to business objectives. You will act as a subject matter expert for AI technologies, helping to define architecture, establish standards, and guide the organisation s AI roadmap while remaining hands-on with implementation. Key Responsibilities Design, develop, and deploy advanced AI and Machine Learning solutions to solve complex business challenges. Lead the architecture and implementation of production-grade AI applications using LLMs, RAG pipelines, AI Agents, and Azure AI services. Provide technical leadership across AI initiatives, ensuring solutions follow best practices for scalability, security, performance, and governance. Own the full AI development lifecycle, from discovery and proof-of-concept through to production deployment and business adoption. Develop and optimise AI models, prompt engineering frameworks, vector databases, and retrieval systems. Design and implement AI agent architectures, workflow automation, and API integrations. Collaborate with Infrastructure and Engineering teams to deploy AI solutions securely within enterprise environments. Ensure solutions leverage Private Endpoints, secure networking, identity management, and enterprise-grade governance controls. Establish monitoring, evaluation, and observability frameworks for AI systems, including hallucination detection, model drift monitoring, performance tracking, and cost optimisation. Partner with operational and commercial stakeholders to identify high-value AI opportunities and define business cases. Measure and report on AI project outcomes, including efficiency gains, automation benefits, cost savings, and customer experience improvements. Mentor and support other technical team members, promoting AI best practices and knowledge sharing across the organisation. Contribute to the development of the organisation s AI strategy, roadmap, and future capability. Required Experience Essential Significant commercial experience in AI Engineering, Machine Learning Engineering, Applied AI, or Data Science roles. Expert-level Python development skills and deep experience with modern AI/ML frameworks and SDKs. Proven experience designing and deploying production-grade RAG solutions and LLM-powered applications. Strong experience building and deploying AI agents, orchestration frameworks, and automated workflows. Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning, or equivalent enterprise AI platforms. Strong understanding of enterprise cloud architecture, including VNets, Entra ID, API Gateways, networking, and secure integrations. Experience deploying and managing AI workloads within production environments. Strong SQL and data engineering skills, working with both structured and unstructured datasets. Ability to translate complex datasets into actionable insights and AI-driven business solutions. Experience implementing AI governance, security, monitoring, and operational best practices. Excellent communication, leadership, stakeholder management, and problem-solving skills. Highly Desirable Strong Data Science background, with experience in statistical modelling, predictive analytics, feature engineering, experimentation, and model evaluation. Experience applying Data Science methodologies to solve complex business problems and identify opportunities for AI adoption. Experience with GenAIOps, LLMOps, MLOps, and AI observability platforms. Exposure to Computer Vision, OCR, Voice AI, Conversational AI, or multimodal AI solutions. Experience working within operational, retail, automotive, logistics, or customer-centric organisations. Knowledge of Responsible AI, AI governance frameworks, and regulatory considerations. Previous experience leading AI initiatives, mentoring engineers, or helping define AI strategy and roadmap. Experience building or contributing to an AI Centre of Excellence or internal AI capability function. What We're Looking For We're looking for someone who combines deep technical expertise with commercial awareness and a pragmatic approach to AI delivery. You'll be comfortable operating at both strategic and hands-on levels, engaging with senior stakeholders while also designing, developing, and deploying solutions yourself. You should be passionate about emerging AI technologies and have a track record of turning innovative ideas into production-ready solutions that create measurable business value. Salary & Benefits Competitive salary depending on experience Quarterly bonus scheme Hybrid working arrangement 3 days in the office / 2 days remote Opportunity to lead and shape enterprise AI capability Exposure to high-profile AI transformation initiatives Strong long-term career progression opportunities Ongoing investment in training, certifications, and professional development Interested? If you're an experienced AI Engineer or Data Science professional looking to take ownership of impactful AI initiatives and help shape the future direction of AI within a growing organisation, we'd love to hear from you. Apply now for the Senior AI Engineer opportunity in Manchester. Senior AI Engineer Manchester
Senior AI Engineer Manchester A growing technology-led business is seeking a Senior AI Engineer to play a pivotal role in shaping and delivering its AI strategy. This is a senior-level, hands-on position responsible for designing, building, and deploying enterprise-grade AI solutions that drive measurable business value across the organisation. Working closely with IT, Data, Engineering, and senior business stakeholders, you will lead the development and implementation of advanced AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Machine Learning, and Azure AI services. You will provide technical leadership, establish best practices, and help build the organisation s long-term AI capability. The business is investing heavily in AI and is looking for someone who can combine deep technical expertise with strategic thinking, taking solutions from concept through to production deployment and adoption. The ideal candidate will have a strong foundation in AI Engineering combined with a robust Data Science background, enabling them to develop, evaluate, and optimise AI solutions that deliver measurable business outcomes. This role would suit an experienced AI professional who enjoys solving complex business challenges, mentoring others, influencing technical direction, and delivering innovative AI solutions at scale. Role Purpose As a Senior AI Engineer, you will lead the design, development, deployment, and optimisation of enterprise AI solutions, ensuring they are secure, scalable, maintainable, and aligned to business objectives. You will act as a subject matter expert for AI technologies, helping to define architecture, establish standards, and guide the organisation s AI roadmap while remaining hands-on with implementation. Key Responsibilities Design, develop, and deploy advanced AI and Machine Learning solutions to solve complex business challenges. Lead the architecture and implementation of production-grade AI applications using LLMs, RAG pipelines, AI Agents, and Azure AI services. Provide technical leadership across AI initiatives, ensuring solutions follow best practices for scalability, security, performance, and governance. Own the full AI development lifecycle, from discovery and proof-of-concept through to production deployment and business adoption. Develop and optimise AI models, prompt engineering frameworks, vector databases, and retrieval systems. Design and implement AI agent architectures, workflow automation, and API integrations. Collaborate with Infrastructure and Engineering teams to deploy AI solutions securely within enterprise environments. Ensure solutions leverage Private Endpoints, secure networking, identity management, and enterprise-grade governance controls. Establish monitoring, evaluation, and observability frameworks for AI systems, including hallucination detection, model drift monitoring, performance tracking, and cost optimisation. Partner with operational and commercial stakeholders to identify high-value AI opportunities and define business cases. Measure and report on AI project outcomes, including efficiency gains, automation benefits, cost savings, and customer experience improvements. Mentor and support other technical team members, promoting AI best practices and knowledge sharing across the organisation. Contribute to the development of the organisation s AI strategy, roadmap, and future capability. Required Experience Essential Significant commercial experience in AI Engineering, Machine Learning Engineering, Applied AI, or Data Science roles. Expert-level Python development skills and deep experience with modern AI/ML frameworks and SDKs. Proven experience designing and deploying production-grade RAG solutions and LLM-powered applications. Strong experience building and deploying AI agents, orchestration frameworks, and automated workflows. Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning, or equivalent enterprise AI platforms. Strong understanding of enterprise cloud architecture, including VNets, Entra ID, API Gateways, networking, and secure integrations. Experience deploying and managing AI workloads within production environments. Strong SQL and data engineering skills, working with both structured and unstructured datasets. Ability to translate complex datasets into actionable insights and AI-driven business solutions. Experience implementing AI governance, security, monitoring, and operational best practices. Excellent communication, leadership, stakeholder management, and problem-solving skills. Highly Desirable Strong Data Science background, with experience in statistical modelling, predictive analytics, feature engineering, experimentation, and model evaluation. Experience applying Data Science methodologies to solve complex business problems and identify opportunities for AI adoption. Experience with GenAIOps, LLMOps, MLOps, and AI observability platforms. Exposure to Computer Vision, OCR, Voice AI, Conversational AI, or multimodal AI solutions. Experience working within operational, retail, automotive, logistics, or customer-centric organisations. Knowledge of Responsible AI, AI governance frameworks, and regulatory considerations. Previous experience leading AI initiatives, mentoring engineers, or helping define AI strategy and roadmap. Experience building or contributing to an AI Centre of Excellence or internal AI capability function. What We're Looking For We're looking for someone who combines deep technical expertise with commercial awareness and a pragmatic approach to AI delivery. You'll be comfortable operating at both strategic and hands-on levels, engaging with senior stakeholders while also designing, developing, and deploying solutions yourself. You should be passionate about emerging AI technologies and have a track record of turning innovative ideas into production-ready solutions that create measurable business value. Salary & Benefits Competitive salary depending on experience Quarterly bonus scheme Hybrid working arrangement 3 days in the office / 2 days remote Opportunity to lead and shape enterprise AI capability Exposure to high-profile AI transformation initiatives Strong long-term career progression opportunities Ongoing investment in training, certifications, and professional development Interested? If you're an experienced AI Engineer or Data Science professional looking to take ownership of impactful AI initiatives and help shape the future direction of AI within a growing organisation, we'd love to hear from you. Apply now for the Senior AI Engineer opportunity in Manchester. Senior AI Engineer Manchester
Square One Resources
Cambridge, Cambridgeshire
Job Title: AI Core Senior Software Developer Location: Cambridge - 3 days a week on-site Salary/Rate: £600-£630/day inside IR35. Start Date: October 2025 Job Type: Contract We are looking for passionate and skilled Software Developers to join our Core AI Services team. In this role, you will help design, develop, and scale AI-enabling platform services and public APIs that are secure, reliable, and cloud-native. These services will act as foundational building blocks for AI adoption across our client's portfolio and partner ecosystem. You will be part of a Scrum team to build innovative, standards-compliant, secure, and production-grade AI capabilities, with a builder mindset - rapid prototyping and continuous improvement with the agility of a start-up. Key Responsibilities: Build scalable, fault-tolerant cloud-native services on Microsoft Azure, ensuring high performance and reliability. 3 Develop secure, well-documented public APIs and SDKs for consumption by internal and external developers. 2 Collaborate with cross-functional teams to deliver end-to-end solutions across data pipelines, orchestration, and service APIs. 3 Embed robust security controls to protect sensitive data and ensure secure access to AI services. 3 Contribute to design reviews, code reviews, and architectural discussions to ensure engineering excellence. 3 Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation. 3 Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development. 2 AI & Cloud Expertise Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability. Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling. Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A). Strong knowledge or experience in working with various ML algorithms (regression, classification, clustering, deep learning) Knowledge of AI ethics and regulations (eg, NIST AI RMF, EU AI Act), and commitment to responsible AI development. Fluent in developing code using AI Tools such as GitHub Copilot. Must be able to use prompt engineering to carry out multiple development tasks. Familiar with AI orchestration, including tools like AI Foundry and/or Semantic Kernel. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/ools such as PyTorch and TensorFlow. Core Skills and Qualifications: Experience in software engineering, preferably in platform or cloud-native service development using Microsoft and .NET technologies. Hands-on experience with Microsoft Azure and associated PaaS services (eg, Azure Functions, AKS, API Management). Strong expertise in RESTful API design, versioning, testing, and life cycle management. Proficient in securing APIs, managing authentication/authorization and data privacy practices. Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions. Experience working in Agile teams and collaborating across global R&D locations Demonstrated ability to mentor junior team members fostering a culture of continuous learning and innovation Demonstrated experience with AI frameworks, tools and Python
Job Title: AI Core Senior Software Developer Location: Cambridge - 3 days a week on-site Salary/Rate: £600-£630/day inside IR35. Start Date: October 2025 Job Type: Contract We are looking for passionate and skilled Software Developers to join our Core AI Services team. In this role, you will help design, develop, and scale AI-enabling platform services and public APIs that are secure, reliable, and cloud-native. These services will act as foundational building blocks for AI adoption across our client's portfolio and partner ecosystem. You will be part of a Scrum team to build innovative, standards-compliant, secure, and production-grade AI capabilities, with a builder mindset - rapid prototyping and continuous improvement with the agility of a start-up. Key Responsibilities: Build scalable, fault-tolerant cloud-native services on Microsoft Azure, ensuring high performance and reliability. 3 Develop secure, well-documented public APIs and SDKs for consumption by internal and external developers. 2 Collaborate with cross-functional teams to deliver end-to-end solutions across data pipelines, orchestration, and service APIs. 3 Embed robust security controls to protect sensitive data and ensure secure access to AI services. 3 Contribute to design reviews, code reviews, and architectural discussions to ensure engineering excellence. 3 Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation. 3 Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development. 2 AI & Cloud Expertise Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability. Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling. Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A). Strong knowledge or experience in working with various ML algorithms (regression, classification, clustering, deep learning) Knowledge of AI ethics and regulations (eg, NIST AI RMF, EU AI Act), and commitment to responsible AI development. Fluent in developing code using AI Tools such as GitHub Copilot. Must be able to use prompt engineering to carry out multiple development tasks. Familiar with AI orchestration, including tools like AI Foundry and/or Semantic Kernel. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/ools such as PyTorch and TensorFlow. Core Skills and Qualifications: Experience in software engineering, preferably in platform or cloud-native service development using Microsoft and .NET technologies. Hands-on experience with Microsoft Azure and associated PaaS services (eg, Azure Functions, AKS, API Management). Strong expertise in RESTful API design, versioning, testing, and life cycle management. Proficient in securing APIs, managing authentication/authorization and data privacy practices. Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions. Experience working in Agile teams and collaborating across global R&D locations Demonstrated ability to mentor junior team members fostering a culture of continuous learning and innovation Demonstrated experience with AI frameworks, tools and Python
