151 to 175 of 254 Retrieval-Augmented Generation Jobs in London

work is genuinely varied: one week you're designing a data API, the next you're improving retrieval quality in a RAG pipeline, the next you're working with infrastructure to get a service into production. We're looking for someone who finds that energising rather than uncomfortable. ...

egress controls). Strong understanding of AI/LLM capabilities and risks across the lifecycle (model onboarding/ingestion, retrieval/RAG patterns, model serving) and associated control points (traceability, access, data handling), including assessing control design and operational effectiveness in fast‐changing environments. Experience with agentic ...

fine-tuning and RAG. Design and implement the context layer-spanning knowledge graphs, vector search, and semantic retrieval-to create reliable, grounded RAG pipelines. Architect foundation model adaptation strategies, including dynamic, cost-and-performance-aware model routing and selection. Design, implement, and prototype high-throughput, low-latency inferencing ...

egress controls). Strong understanding of AI/LLM capabilities and risks across the lifecycle (model onboarding/ingestion, retrieval/RAG patterns, model serving) and associated control points (traceability, access, data handling), including assessing control design and operational effectiveness in fast-changing environments. overseeing "Claude Code"-style ...

collaborate with product teams to deliver reliable AI tooling. The role requires strong Python, expertise with LLM frameworks, FastAPI, and Kubernetes, plus experience with RAG and tool orchestration in an enterprise setting. #J-18808-Ljbffr ...

customer‐facing team in a cloud computing environment. Experience developing AI/Generative AI solutions utilizing AI tools and designing multi‐agent workflows and RAG systems. Experience in people management. Preferred qualifications Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience in architecting ...

launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain, a Security Check ...

ship Experience building or deploying AI/LLM systems in production Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with ...

experience with software development using Python or similar coding languages. Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g. ...

Have Passion for or experience in e-learning projects is a strong bonus Hands-on experience building AI-powered features (e.g. LLM integrations, RAG, AI-assisted user experiences) is a strong bonus Experience running and monitoring AI products in production: evals, output quality tracking, and observability specific to AI/ ...

Guide architecture across teams, helping reduce complexity and establish common patterns. Partner with AI and Retrieval teams to build scalable search and RAG capabilities. Lead complex cross‐team technical initiatives from design through production. Improve platform reliability, scalability, observability, and developer experience. Contribute hands‐on to critical technical … team technical initiatives. Experience with cloud infrastructure (AWS), Kubernetes, APIs, and modern backend development. Familiarity with AI‐powered systems, Retrieval‐Augmented Generation (RAG), search platforms, or vector databases. Strong programming experience in Python or another modern backend language. Comfortable influencing technical direction without direct ...

across microservices to identify and resolve failures in real‐time. Experience connecting agents to enterprise knowledge bases and optimizing Retrieval‐augmented generation (RAG) chunking to prevent hallucinations. Ability to travel up to 50% of the time. Track record of troubleshooting live, high‐traffic systems ...

Significant experience shipping AI agents and LLM systems into production, with strong opinions on the modern toolkit — eval frameworks, agent orchestration, RAG pipelines, prompt engineering — and the tradeoffs between them. A track record of taking ambiguous problems from zero to one, raising the bar for the engineers around ...

LLMs, prompt design, and agent orchestration Strong Python skills and solid backend/API fundamentals Experience with data pipelines, embeddings, retrieval, or RAG systems Product‐driven mindset with comfort operating in ambiguity Ability to reason about latency, cost, reliability, and quality trade‐offs Excellent communication and ownership mentality ...

Python code Solid understanding of backend systems and APIs, even if not infrastructure-focused Experience working with data pipelines, embeddings, retrieval, or RAG-style systems Ability to reason about latency, cost, reliability, and quality trade-offs Product mindset You naturally think in terms of user outcomes, not just ...

scaling AI‐enabled products, internal platforms, workflow tools, agents, or automation capabilities. Experience with AI product evaluation, model performance, responsible AI, prompt design, RAG, knowledge graphs, or agent orchestration. Experience in financial services, capital markets, asset servicing, banking, payments, operations, risk, compliance, or data‐intensive enterprise environments. Experience working ...

/AI, guiding customers and the Field Engineering team to design production‐grade AI solutions on the Databricks platform. You will drive GenAI initiatives, RAG architectures, agentic systems, AI observability, and NLQ of structured data, while mentoring peers and influencing the platform roadmap. Some travel may be required. #J ...

move fast and safely at scale. You will collaborate with backend and AI engineers to deliver production-grade AI capabilities, including Agentic AI, RAG, embeddings, and vector search, while building secure deployment pipelines and observability across systems. #J-18808-Ljbffr ...

/ML projects, mentor teammates, and ship models into production, balancing quick wins with robust engineering. Focus areas include AI/OCR workflows, RAG systems, and deploying models on AWS with SageMaker/Bedrock. This hybrid role requires 1–2 days in Central London per week and right to work ...

Engineer | £80,000 - £110,000 | London/Hybrid | Python | LLM | GenAI | RAG | AI Agents | Looking to join one of the fastest growing AI companies in Europe Want to have autonomy and own end-to-end solutions I am currently supporting a brilliant AI company who are looking ...

through technical leadership, innovation initiatives and mentoring. Responsibilities Lead engineering teams delivering Generative AI solutions. Design and build scalable full‐stack AI applications. Develop RAG pipelines, AI agents and LLM‐powered platforms. Define technical architecture and engineering best practices. Drive delivery from proof‐of‐concept to production deployment. Engage directly ...

build business cases, and define practical implementation roadmaps. Provide technical leadership across AI technologies Lead across modern AI architectures, Generative AI, Agentic AI, LLMs, RAG, Data Platforms, Cloud AI Services, and enterprise integration patterns. Remain hands-on where required Provide architectural guidance, technical assurance, innovation leadership, and support the resolution ...

experience with software development using Python or similar coding languages. Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g. ...

issues, and have informed opinions on AI/ML system architecture AI‐serious: you've led or contributed to shipping LLM‐powered systems (agents, RAG, evaluation infrastructure) in production, and you have opinions on what works Comfortable with the player‐coach archetype: you don’t want to stop being technical ...

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 ...