19 of 19 Remote Retrieval-Augmented Generation Jobs in Central London

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term … cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI innovation, where your work will directly shape how next-generation systems interact, reason, and assist. More ❯

with a world-class team of engineers, researchers, and product thinkers to bring AI features to life. Design and maintain retrieval-augmented generation (RAG) and agentic systems that power real-world use cases. Stay ahead of the curve by experimenting with the latest in AI research and tooling—and bring those ideas to production. … passion for solving hard problems with elegant code. Excellent communication skills—you can explain complex ideas clearly to both technical and non-technical audiences. 💡 Bonus Points For Experience with RAG pipelines and improving retrieval performance. Contributions to open-source AI projects. A portfolio of AI-powered products or prototypes you’ve helped bring to life. 🚀 Why You’ll More ❯

of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering More ❯

and maintaining long-lived systems. Bonus Points for: Familiarity with financial services or private equity environments. Experience with Azure, Postgres, Streamlit, or similar tools. Practical experience with document-based RAG, Q&A, or fact extraction tasks. Thriving in small teams with fast feedback and iteration loops. Please, apply to learn more. More ❯

LLM-based UIs Awareness of AI governance , model auditing, and data privacy regulation (GDPR, DPA, etc.) Familiarity with reinforcement learning, retrieval-augmented generation (RAG), or dynamic reasoning workflows Offer Details 💼 Role Type: Contract (outside IR35) or Permanent 💸 Compensation: Market rates or six-figure salary 📍 Location: London EC4| Hybrid (some remote) 🗓️ Start Date: August More ❯

nationwide rollout, while setting the gold-standard for safety, ethics, and governance in a regulated environment. As Director of AI & Research you will spearhead conversational AI, design next-generation AI-powered care models, and define rigorous guardrails to ensure the safety and confidentiality of all users. This is an opportunity to work on greenfield challenges, hands-on experimentation … the roadmap for conversational AI, generative LLMs, and predictive care models from ideation to production. Lead cutting-edge research - run rapid experiments, RLHF loops, fine-tuning, and retrieval-augmented generation to push the boundaries of clinical dialogue systems. Architect safe, scalable solutions - design reference & MLOps architectures on cloud with robust guard rails in place. More ❯

Mid-Level AI Engineer | AI-Driven Digital Transformation Salary: Up to £75,000 plus benefits Technology: Python, Microservices, CI/CD, AI/ML, LLM or RAG Location: Hybrid/London (onsite twice a week) Multiple Vacancies An innovative, fast-growing company transforming digital client experiences through intelligent technology is seeking a number of Mid-Level AI Engineers to join … Python programming skills with backend development experience Interest or hands-on exposure to AI/ML concepts, particularly LLMs and Retrieval-Augmented Generation (RAG) Experience working with AWS or similar cloud platforms Understanding of microservices architecture and distributed systems Familiarity with container tools such as Docker and Kubernetes Experience with CI/CD tools More ❯

London) One of the UK’s most technically ambitious GenAI startups is hiring an AI Software Engineer to join their core team building the brains behind a next-generation enterprise platform. Backed by $15M in Series A funding from top-tier VCs (early investors in Deliveroo and GoCardless), this company is automating the development of custom software using … through AI. You’ll work closely with a former FAANG engineering lead who spent over a decade building LLM-based dev tools, using a stack that includes Python, LangChain, RAG, Rust, and Kubernetes. They’re looking for engineers with: A STEM degree (BSc or higher) from a top ranked university 3+ years of Python experience and exposure to Go and More ❯

Founding Engineer Location: Hybrid (2–3 days/week in London office) I am representing a fast-moving, mission-driven start up building an AI-powered clinical knowledge platform. What You’ll Do: Build and scale backend services (Python/ More ❯

Engineer The role is building AI based automation into back-office administration tasks. You'll be working with GenAI and Agentic AI, lots of AWS, NodeJS, Python, HuggingFace, LangChain, RAG techniques, interfacing with diverse data sets. The opportunity Work at the forefront of the industry. It's exciting, competitive, fast paced and challenging of course! You'll have the support More ❯

Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel training etc The role is hybrid, with adhoc requirements to be on client premises (London) this could be between 1-3 days a week, so we would More ❯

object detection (e.g. MobileNet, YOLO). Either way, we’re looking for someone who can help our app understand what the visitor is looking at – reliably and at scale. RAG Systems, Data Pipelines & Internal Agents: You'll design the data pipelines that power our AI features, including retrieval-augmented generation (RAG), internal LLM-based More ❯

time using image embeddings, similarity search (e.g. CLIP, vector search), and traditional CV approaches (e.g. YOLO, MobileNet). 🔹 LLM & RAG Systems: Design and implement pipelines that support retrieval-augmented generation, internal AI tools, and scalable content delivery. Experience with vector databases, agent frameworks, or data workflows is highly relevant. 🔹 Deployment & MLOps: Own model deployment More ❯

object detection (e.g. MobileNet, YOLO). Either way, we’re looking for someone who can help our app understand what the visitor is looking at – reliably and at scale. RAG Systems, Data Pipelines & Internal Agents: You'll design the data pipelines that power our AI features, including retrieval-augmented generation (RAG), internal LLM-based More ❯

object detection (e.g. MobileNet, YOLO). Either way, we’re looking for someone who can help our app understand what the visitor is looking at – reliably and at scale. RAG Systems, Data Pipelines & Internal Agents: You'll design the data pipelines that power our AI features, including retrieval-augmented generation (RAG), internal LLM-based More ❯

Job Title: Data Scientist Location: London, UK (Hybrid) Job Type: Permanent Job Description: Experience: Minimum of 8+ years. Skilled Required: LLM, RAG, Finetuning, NLP, Text Summarisation, ML, Feature Engineering Llamaindex, LangChain, LangSmith Vector DB, Vector Search, FAISS Embeddings Experience with OCR, layout models PDF and text file parsing, along with various other file types Experience with REST API More ❯

teams reach high-intent buyers through hyper-personalised, multi-channel campaigns. We’re building an AI-first platform from the ground up, with LLMs powering everything from content generation to strategic recommendations. We’re looking for hands-on AI Fullstack Product Engineers who’s excited to build, ship, and fully own production-grade AI features. You’ll have … ll be responsible for architecting and shipping AI-powered features using tools like PydanticAI, LangGraph, FastAPI, and OpenAI/Anthropic APIs. You’ll build and orchestrate intelligent agents and RAG pipelines, moving quickly to prototype, test, and launch in days, not months. Working closely with product, design, and go-to-market teams, you’ll build features that solve real customer More ❯

and verifiable in our product, whether that’s code or more unstructured outputs. We have frameworks for evaluation, verification, specialized code and test generation pipelines, agentic behavior, RAG, observability and orchestration tooling, and many more... all widely used across our product, neatly integrated, and informed by real customer and product needs. Each of these are constantly evolving to … necessary. You either have professional experience using LLMs or have enthusiastically experimented in your own time. Industry experience with LLM toolchains and ecosystems (e.g. libraries like Langchain, observability tooling, RAG systems, etc.) is a plus. You have a fundamental understanding of code analysis, compilers, domain-specific languages, or related topics, and are keen to learn in this area. You are More ❯

platform like Kubeflow. Demonstrated ability to transition models from prototype to production. Experience assessing various AI/ML technologies and models for fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI More ❯