151 to 175 of 304 Retrieval-Augmented Generation Jobs in the UK

shipping reliable systems used by real customers. Key responsibilities Build and deploy LLM-powered features across drafting, prosecution, and litigation workflows Design and maintain RAG pipelines over large, complex legal and technical corpora Own systems from prototype through to production Focus on robustness, evaluation, and reliability in precision-critical ...

deployment and monitoring. Lead end to end delivery of AI and LLM based solutions across underwriting and insurance journeys Build and deploy agentic workflows, RAG pipelines, and LLM powered applications for internal and customer facing products Work across structured and unstructured data, collaborating closely with Machine Learning and GenAI specialists ...

They’re Looking For Proven experience designing & deploying AI/ML solutions Expert knowledge of LLMs, AI frameworks & agent-based systems Experience in building RAG Systems Cloud expertise across AWS/Azure/GCP Ability to turn complex problems into scalable architectures Passion for AI innovation (this ...

deployments Data & Analytics ETL/ELT pipelines ERP/CRM integrations Analytics environments KPI engines Dashboards and reporting Data-intensive enterprise applications AI LLMs RAG architectures AI orchestration AI-enabled workflows Production AI implementation AI-assisted engineering workflows Comercial Platforms Enterprise business workflows User entitlements & permissions Subscription/pricing-linked ...

performance and compliance standards. Discover the responsibilities Define standardised evaluation rubrics and scoring systems for system performance and safety across various AI archetypes including RAG and agentic workflows Design comprehensive test cases covering deterministic logic and adversarial scenarios to stress test AI outputs Implement automated evaluators such ...

business environment Deep expertise in Python and modern AI/ML frameworks and SDKs Strong experience building and deploying production-grade AI solutions, including RAG pipelines and LLM-based applications Hands-on experience with AI deployment, operationalisation, monitoring, and scaling Strong understanding of enterprise infrastructure concepts including VNets, Entra ...

software engineering best practices. Support end-to-end MLOps processes including deployment, monitoring and model validation. Explore and implement generative AI capabilities including LLMs, RAG pipelines, and intelligent workflow automation. Key Skills: Commercial experience in Machine Learning Engineering, Applied AI, or related software engineering roles. Strong programming skills in Python … pipelines, and scalable deployment practices. Understanding of MLOps concepts including experiment tracking, model monitoring, and reproducibility. Exposure to Generative AI technologies including LLMs, RAG, or prompt engineering is a plus. Strong communication skills and ability to work effectively within cross-functional agile teams. ...

real-world systems. What you'll work on: Integrating AI components (including LLMs) into production applications and workflows Designing and implementing RAG (Retrieval-Augmented Generation) systems Evaluating LLM behavior, identifying failure modes, and implementing mitigation strategies Testing and debugging non-deterministic AI systems …/CD, IaC, testing, containers) Practical experience with AI systems, including LLM behavior and architectures Evaluation techniques and failure mode analysis Experience with RAG and applied AI system design Strong understanding of AI limitations and appropriate use cases Excellent communication and stakeholder engagement skills Eligibility for UK SC-level security ...

Requirements Proven experience leading Data Science, Machine Learning or GenAI initiatives within complex organisations Experience building and deploying LLMpowered applications Strong knowledge of RAG, embeddings, vector databases and retrieval architectures Experience with Azure, Databricks and modern cloudbased AI platforms Track record delivering AI solutions into production environments Experience ...

working across: Microsoft Azure (including AI services/Foundry) .NET and modern backend engineering APIs, microservices and DevOps practices GenAI/LLM tooling (RAG, prompt engineering, embeddings, vector search) This is a role for someone who enjoys solving challenging problems and building robust, real-world systems in a fast-moving ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

Requirements AWS Bedrock Expert: Hands-on experience with Bedrock Agents, Knowledge Bases, and model lifecycle management. AI/ML Depth: Strong grasp of FMs, RAG, tool-use, and the failure modes of agentic workflows. Security & Compliance: Deep knowledge of NIST AI RMF, OWASP LLM Top 10, and UK/ ...

clear focus on technical leadership, ownership and delivery in complex environments . We’re looking for engineers and leaders across: AI Engineering (LLMs, RAG, Applied AI systems) Machine Learning Engineering (model development, optimisation, deployment) Data Engineering (Spark, Databricks, cloud data platforms) Full Stack Software Engineering (end-to-end system ownership ...

into CI/CD pipelines and wider SDLC activities. Should have: Practical exposure to testing AI/ML/LLM‐based systems (e.g. chatbots, RAG applications, AI‐assisted workflows) and an interest in deepening this. Familiarity with approaches to evaluating LLM outputs (for example, semantic‐similarity based methods or using ...

London office 1-2 times per week. WHAT YOU BRING 5+ years hands-on experience building and deploying production-grade AI systems using LLMs, RAG pipelines, MCPs and agentic workflows A track record of leading complex, client-facing technical engagements Strong system design and architecture skills, with the ability ...

senior client stakeholders to shape and deliver solutions Build and deploy end-to-end AI products , not just prototypes Apply technologies such as LLMs, RAG systems, and agentic workflows to real business problems Translate technical outputs into clear commercial value and measurable impact Mentor and develop consultants, helping build capability ...

small team, wearing multiple hats, and moving at speed without heavy process. AI/LLM experience (a plus) : Experience building with AI agents, RAG systems, or LLM-powered features is valuable but not required. End-to-end ownership mindset : You've shipped something meaningful on your own—a project, open ...

Product — influencing roadmap, shaping requirements, and bridging technical and commercial priorities Hands-on experience with AI/ML integration — whether LLM APIs, prompt engineering, RAG architectures, or embedding AI tooling into production software Deep understanding of modern software design patterns and best practices Hands on experience with cloud based architectures ...

approach with proven experience or strong hands-on interest in Azure's AI stack, including Azure AI Foundry, Azure OpenAI, AI Search, agents and RAG patterns. Strong practical knowledge of databases, including SQL and NoSQL platforms, schema design, data access patterns, query performance and secure data handling. Ability to design … OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure SQL, Cosmos DB, AKS, storage services and related platform components. Contribute to AI and RAG features, including document ingestion, metadata enrichment, retrieval workflows, grounding, reasoning flows, template generation and agent orchestration. Support Microsoft Fabric and data ...

approach with proven experience or strong hands-on interest in Azure's AI stack, including Azure AI Foundry, Azure OpenAI, AI Search, agents and RAG patterns. Strong practical knowledge of databases, including SQL and NoSQL platforms, schema design, data access patterns, query performance and secure data handling. Ability to design … OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure SQL, Cosmos DB, AKS, storage services and related platform components. Contribute to AI and RAG features, including document ingestion, metadata enrichment, retrieval workflows, grounding, reasoning flows, template generation and agent orchestration. Support Microsoft Fabric and data ...

this Senior Consultant role, you will operate as a hands-on engineer within a squad, designing and implementing AI capabilities such as agents, RAG pipelines and supporting services while ensuring solutions meet enterprise standards for reliability, security and governance. What you'll do Client-facing engineering & delivery Collaborate with client … audiences. Support the adoption of delivered solutions through testing, iteration and feedback cycles. Solution design & implementation Design and implement AI-enabled components such as RAG pipelines, agents and supporting microservices. Integrate solutions with enterprise data sources, APIs and existing platforms while maintaining reliability and security standards. Apply responsible-AI guardrails ...

Contract: Permanent, Full-time About the Company We're partnering with a growing technology-focused business investing heavily in AI, automation, and next-generation digital platforms. The company is building AI-enabled tools and intelligent internal systems designed to improve operations, workflows, and decision-making across the organisation. … MLOps tooling including Docker, Kubernetes, CI/CD, monitoring, and logging Comfortable operating in fast-paced, product-led environments Nice to Have Experience with RAG pipelines, vector databases, or AI agents Exposure to machine learning workflows and applied AI systems Experience building internal AI platforms, copilots, or automation tools Startup ...

backend engineering, and cloud systems , designing and deploying intelligent features that directly impact users. Expect to: Design and implement LLM-based applications (RAG pipelines, agents, copilots) Build scalable backend services using Python and Java Integrate AI into existing cloud-native SaaS platforms Own the full lifecycle: experimentation prototyping production Optimise … software engineering, with strong experience in Python and/or Java Hands-on experience working with LLMs (prompt engineering, fine-tuning, embeddings, vector databases, RAG) Experience building and deploying applications in cloud environments (Azure preferred, AWS/GCP also considered) Strong understanding of APIs, microservices, and distributed systems Familiarity with ...

Leading a team of Data Scientists and AI specialists Defining Data & AI strategy and technical direction Designing and delivering Machine Learning, NLP, GenAI and RAG-based solutions Working directly with senior business stakeholders and clients Translating complex technical concepts into clear business language Driving delivery of AI products from concept ...