51 to 75 of 76 Retrieval-Augmented Generation Jobs in London

AI pipelines. What You'll Bring Deep solution architecture experience across cloud, data, and business platforms. Proven experience designing or integrating AI/GenAI solutions such as copilots, chatbots, RAG systems, or automation tools. Understanding of GenAI and agentic design patterns, including orchestration frameworks and RAG. Experience with event-driven systems, messaging platforms, and APIs. Familiarity with AI governance standards More ❯

conducting cutting-edge applied research in LLMs, Gen AI, and related areas. Responsibilities and Impact Design solutions utilizing natural language processing (NLP) models, including chat assistants and retrieval-augmented generation systems. Develop Large Language Model (LLM) solutions that incorporate prompt engineering techniques, model fine-tuning, and alignment strategies. Evaluate NLP models using both human More ❯

goals into clear technical execution through strong communication and cross-team alignment. Nice to Have Experience with orchestration frameworks ( LangChain, LangGraph ) and multi-agent workflows Knowledge of vector databases, RAG pipelines, and lightweight model hosting Ability to design data pipelines and feedback loops for improving AI-driven features Awareness of emerging AI areas such as multimodal, edge AI, or AI More ❯

Docker, Kubernetes, and containerized applications, Expert knowledge of TypeScript, Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping), Hands-on experience with LLM APIs, embeddings, or RAG patterns Track record of delivering user-facing software at scale. Interview process After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes More ❯

tools for modelling. Working experience on Modern data platforms which involves Cloud & related technologies Keeps track of industry trends and incorporates new concepts Advanced understanding of AI concepts , LLMS, RAG, Agentic apps Advance Understanding in Data visualization and Data pipelines. Excellent understanding of traditional and distributed computing paradigm. Experience in designing and building scalable data pipelines. Should have excellent knowledge More ❯

tools for modelling. Working experience on Modern data platforms which involves Cloud & related technologies Keeps track of industry trends and incorporates new concepts Advanced understanding of AI concepts , LLMS, RAG, Agentic apps Advance Understanding in Data visualization and Data pipelines. Excellent understanding of traditional and distributed computing paradigm. Experience in designing and building scalable data pipelines. Should have excellent knowledge More ❯

tools for modelling. Working experience on Modern data platforms which involves Cloud & related technologies Keeps track of industry trends and incorporates new concepts Advanced understanding of AI concepts , LLMS, RAG, Agentic apps Advance Understanding in Data visualization and Data pipelines. Excellent understanding of traditional and distributed computing paradigm. Experience in designing and building scalable data pipelines. Should have excellent knowledge More ❯

tools for modelling. Working experience on Modern data platforms which involves Cloud & related technologies Keeps track of industry trends and incorporates new concepts Advanced understanding of AI concepts , LLMS, RAG, Agentic apps Advance Understanding in Data visualization and Data pipelines. Excellent understanding of traditional and distributed computing paradigm. Experience in designing and building scalable data pipelines. Should have excellent knowledge More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

them for production, and putting the right evaluation and governance around them. What you'll do Build GenAI tools end-to-end (independently): chat/assistants, document Q&A (RAG), summarisation, classification, extraction, and workflow/agent automations. Own evaluation & safety : create offline/online eval sets, measure faithfulness/hallucination, bias, safety, latency and cost; add guardrails and red … ability to ship independently : from idea prototype secure, supportable production tool. Strong Python & SQL ; solid software engineering habits (testing, versioning, CI/CD). Practical LLM skills: prompt design, RAG , tool/function calling, evaluation & guardrails , and prompt/model observability. Sound grasp of statistics/experimentation (A/B tests, hypothesis testing) and communicating impact to non-technical audiences. More ❯

employee queries, policy navigation). Design and deploy conversational agents using LangChain and AutoGen for internal use. Build modular and scalable pipelines using LangGraph for multi-agent orchestration. Integrate RAG systems to enable context-aware document retrieval from internal HR/legal databases. Required Skills & Experience: Solid exposure in AI/ML engineering, with a strong focus on … NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability to translate technical concepts for non-technical More ❯

employee queries, policy navigation). Design and deploy conversational agents using LangChain and AutoGen for internal use. Build modular and scalable pipelines using LangGraph for multi-agent orchestration. Integrate RAG systems to enable context-aware document retrieval from internal HR/legal databases. Required Skills & Experience: Solid exposure in AI/ML engineering, with a strong focus on … NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability to translate technical concepts for non-technical More ❯

Working at the forefront of Generative AI, this role is ideal for Applied AI Engineers who thrive in fast-paced environments and want to help shape the next generation of AI applications for well-known brands. From sports broadcasters to Tier 1 banks. What You'll Need: Proven ability to develop and deploy end-to-end, scalable … AI solutions using Python programming Solid understanding of microservices architecture, CI/CD (Github Actions) and data pipelines powering AI-driven applications Deep knowledge of LLMs, fine-tuning, prompting, RAG and Agentic frameworks. Especially integration with the OpenAI API GPT, Gemini, LLama, Claude etc. Experience designing and implementing robust quality assurance/testing frameworks for AI performance Ability to collaborate … you know your way around all the following: Langchain, Lang graph, Agentic Frameworks, LLarma Python, JavaScript, TypeScript, AWS/GCP/Azure, Spark/Data Bricks, FastAPI/Flask, RAG, LLMs, GenAI, AI Solutions, Data Pipelines, Microservices, Solution Design, Software Development, Restful APIs, Chatbots, CI/CD Github Actions, AI Engineering, Unit Testing, Vector Databases Please note: This role does More ❯

applying large language models to complex, real-world problems , Strong proficiency in Python and ML frameworks (PyTorch, JAX, TensorFlow, Hugging Face Transformers) , Hands-on experience with advanced LLM techniques: RAG systems, chain-of-thought prompting, agentic tool use, and multi-agent coordination , Experience with distributed systems, cloud platforms, and scalable ML infrastructure , Knowledge of prompt engineering, LLM fine-tuning, and … reasoning capabilities , Platform: Create and maintain the scalable infrastructure that allows thousands of AI agents to interact, communicate, and evolve within complex simulations , LLM Solutions: Design advanced prompting strategies, RAG systems, and tool-use frameworks that enable agents to access information and take actions in their environment , Optimization: Ensure our agent systems can scale efficiently, optimizing for both computational performance More ❯

Full Stack AI Software Engineer - Full Remote UK - £90,000 + Equity This role requires a software engineer with experience in implementing RAG pipelines and Vector Search (and hybrid AI searches, preferably). The client I am working with is an AI focused start-up backed by a £1.7M pre-seed investment. They are on a mission to streamline the … an early stage. What you'll work on: Backend APIs (Python/FastAPI): Build and maintain secure, high-performance services that drive AI features and data access at scale. RAG & vector search: Design and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate … AI development. Requirements: A motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient More ❯

Team, you'll design and build next-generation automation platforms, blending Python, React, Postgres, and modern DevOps practices with cutting-edge AI/ML techniques such as RAG, vector databases, and multi-agent systems. You'll work across the full software lifecycle: from system design and test automation, to deployment and performance monitoring, collaborating with some of the … in the industry. What You'll Work On Designing and developing automation solutions aligned with Apple's product requirements. Building agentic AI/ML systems (MCP servers/clients, RAG pipelines, vector DBs). Developing both front-end (React, JS) and back-end (Python, APIs, Postgres) features. Driving test automation with Selenium and iOS functional frameworks. Implementing CI/CD … experience with Selenium and iOS functional automation. Strong React/JavaScript UI development background. Back-end engineering with Python + Postgres. AI/ML expertise in LLMs, embeddings, and RAG systems. Experience with ETL pipelines, vector databases, and modern DevOps (Jenkins). Bonus points for: Multi-agent system design. Graph database experience. Familiarity with Charles Proxy, Git, Jenkins. Role Details More ❯

the ground up. This role is all about turning AI into action: you'll partner with domain experts to build bespoke LLM-powered apps (like internal Co-Pilots and RAG systems), drive adoption across teams, and embed models directly into business processes. Think real impact, not just proof of concept. What You'll Do Build and deploy AI products using … scale, and refine models in production What You'll Bring 6-8 years of applied AI/ML experience, ideally with LLMs and enterprise deployment Hands-on experience with RAG systems, agentic workflows, and Azure ML tools Confidence working with business users to design AI tools they'll actually use A pragmatic, value-first mindset and strong communication skills Why More ❯

serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to More ❯

serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to … will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Please Note: We have offices in London, Toronto, San Francisco, New York but also embrace being remote-friendly More ❯

AI Engineer - Defence RAG Systems ( Security Clearance Essential ) Clearance: Active SC Essential | Sector: Defence Role Overview Defence client requires an SC Cleared AI Engineer to build fully on-premises RAG systems using open-source technologies. You'll develop classified AI capabilities on air-gapped infrastructure with zero external dependencies. Key Responsibilities - Build end-to-end RAG pipelines on isolated defence … if required - Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises - Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments - Strong vLLM/Text Generation Inference experience for high-throughput model serving - Proven ability to work on air-gapped systems with no external package repositories - Experience with GPU orchestration (NVIDIA A100/H100) and More ❯

AI Engineer - Defence RAG Systems ( Security Clearance Essential ) On Site 2 X Days a week, Plymouth Clearance: Active SC Essential | Sector: Defence Role Overview Defence client requires an SC Cleared AI Engineer to build fully on-premises RAG systems using open-source technologies. You'll develop classified AI capabilities on air-gapped infrastructure with zero external dependencies. Key Responsibilities - Build … end-to-end RAG pipelines on isolated defence networks using open-source LLMs (Llama 3, Mistral, Qwen) - Deploy local vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for … if required - Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises - Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments - Strong vLLM/Text Generation Inference experience for high-throughput model serving - Proven ability to work on air-gapped systems with no external package repositories - Experience with GPU orchestration (NVIDIA A100/H100) and More ❯

AI platform. We're building a new team in London and hiring for a Senior Forward Deployed Engineer to help enterprise clients unlock the full power of LLM + RAG technology What you'll do Work directly with enterprise clients to turn business needs into live AI use cases Lead proof of concepts (pre-sales) and guide customers through onboarding … directly with enterprise customers (consulting, workshops, exec comms) Development skills are desirable (Python/JavaScript/TypeScript) for prototypes and integrations Strong understanding of AI/LLM concepts (prompting, RAG) Track record in digital experience or enterprise SaaS Highly desirable but not a showstopper A significant background in the Digital Experience Platform (DXP) On offer OTE of circa 115k, plus More ❯