76 to 100 of 153 Retrieval-Augmented Generation Jobs in London

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/ ...

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 ...

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 ...

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 ...

. AWS Bedrock Stack: Hands-on experience with Agents, Knowledge Bases, Guardrails, and model lifecycles. AI/ML Core: Mastery of FMs, RAG, tool-use, and non-deterministic agent logic. Security Frameworks: Proficiency in OWASP LLM Top 10 and NIST AI RMF . Role 1: Identity Expert Mission: Secure ...

tooling. Strong numerical reasoning. Top-uni CS/maths/engineering/science, or equivalent in what you've built. Shipped production LLM systems — RAG, prompting, agents. The kind customers pay for. You've worked somewhere fast — startup or strong tech team — and make good calls on imperfect information. ...

multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout … Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI-enabled solutions Exposure to cloud and modern data platforms Financial ...

application Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques likeparameterefficient fine-tuning (PEFT) (e.g., LoRA, QLoRA). Implementing Retrieval-Augmented Generationpipelines to enhance the knowledge and accuracy of LLMs. Utilizing vector databases for efficient storage andretrieval of embeddings generated by LLMs. rafting ...

adaptive AI architectures Implementing prompt engineering at production scale Developing and managing multi-agent workflows Optimising retrieval systems and memory strategies (RAG architectures) Requirements 5+ years commercial experience with Python/PHP Proven experience delivering production-grade AI systems (not just prototypes) Hands-on experience building autonomous systems ...

Python and FastAPI on the backend, React and TypeScript on the frontend, Postgres, ElasticSearch and vector databases for data, and LLMs, agents and RAG across the AI layer. What they're looking for Has built and managed an engineering team through a high-growth scaling phase, not just inherited ...

self-service tooling for model evaluation, prompt engineering, A/B testing, monitoring, and compliance validation Establish and evolve patterns for data pipeline management, RAG/retrieval design, model versioning, endpoint management, and agentic orchestration Develop comprehensive documentation, architectural guidance, runbooks, and examples that reduce onboarding time … technical audiences AI/ML & Ecosystem Knowledge Hands-on experience with LLMs, agentic frameworks, and GenAI tooling (models, APIs, orchestration platforms) Practical experience with RAG architectures, prompt engineering, fine-tuning workflows, and multi-agent systems Experience with SDLC acceleration using AI (e.g., copilot-style tools, automated testing, code generation ...

deliver solutions that create measurable commercial impact. What you'll be doing • Designing enterprise AI and GenAI architectures • Building scalable solutions across LLMs, RAG and Agentic AI • Defining AI platform, governance and deployment strategies • Advising senior stakeholders on AI adoption and transformation • Working across engineering, cloud, data and business teams … Driving AI from proof of concept to enterprise-scale delivery Technology Python, LLMs, RAG, Agentic AI LangChain, LangGraph Vector Search & Semantic Retrieval MLOps & LLMOps AWS, Azure, GCP, Databricks Kubernetes & Cloud-Native Platforms We're looking for • Experience designing enterprise AI, ML or data platforms • Strong cloud and modern ...

knowledge graph accurately and consistently Design and optimise Cypher queries for agent consumption, analytics and operational reporting Integrate the knowledge graph with LLM and RAG architectures to support AI agent knowledge retrieval Implement GraphRAG patterns to enable agents to traverse and reason over graph-structured knowledge Ensure graph … networkx, rdflib, py2neo) SQL Bash/Shell Scripting REST API integration GraphQL JSON-LD processing AI & Cloud Architecture AI Integration Cloud Platforms Governance & Operations RAG architecture design GraphRAG implementation Vector database integration LLM knowledge grounding Semantic retrieval design Agent knowledge API design AWS (Neptune, Glue, S3, Lambda) Azure ...

doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy … Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment ...

years' experience building production-grade ML, data or software systems Proven experience deploying NLP or LLM-based features into production environments Strong exposure to RAG, retrieval or recommendation systems Experience working with vector databases and end-to-end LLM workflows Familiarity with graph databases and cloud data platforms ...

zones, networking, security, governance) Design scalable cloud, data, and AI solutions Deliver modern data platforms (Fabric, Databricks, data lakes) Shape AI solutions (Azure OpenAI, RAG, copilots) Run client workshops and act as technical lead on engagements Support pre-sales, bids, and solution design What Were Looking For 610+ years Azure ...

zones, networking, security, governance) Design scalable cloud, data, and AI solutions Deliver modern data platforms (Fabric, Databricks, data lakes) Shape AI solutions (Azure OpenAI, RAG, copilots) Run client workshops and act as technical lead on engagements Support pre-sales, bids, and solution design What We’re Looking For 6–10+ ...

turning ambition into actionable strategy across the business. You’ll work at the intersection of business and technology, translating AI capabilities (LLMs, document intelligence, RAG) into commercially meaningful initiatives across domains such as customer, operations, and risk. Rather than delivering isolated use cases, your focus will be on building ...

will be involved across the full lifecycle of GenAI productsfrom proof of concept through to scalable production deployment and monitoring. Working with modern LLMs, RAG architectures and agentic frameworks , youll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities … Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models) Build and deploy RAG systems using vector databases and semantic search Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar Create effective prompt engineering strategies with appropriate guardrails for production systems Implement monitoring ...