26 to 50 of 279 Retrieval-Augmented Generation Jobs in the UK

about building intelligent, agentic systems using LangGraph. If you thrive at the intersection of LLMs, automation, and complex system design, this is your chance to shape the next generation of AI infrastructure. What You’ll Do Design, implement, and optimize LangGraph-based AI workflows and multi-agent systems Integrate LLMs, APIs, and data pipelines into production-ready solutions … contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a bias toward action and experimentation Nice to Have Experience More ❯

growing sports tech company. Role and Responsibilities: Design, build, and deploy Large Language Model (LLM)-driven applications into production Develop retrieval-augmented generation (RAG) systems for real-time insights from performance and wearable data Optimise and fine-tune LLMs for efficiency, scalability, and accuracy in production environments Build and maintain robust data pipelines and … AI Engineering experience, with strong software engineering fundamentals Proven experience working with LLMs in production (fine-tuning, prompt engineering, or API integrations) Proficiency in Python Experience designing and deploying RAG pipelines (vector databases, embeddings, retrieval optimisation) Academic Excellence: BSc or MSc in Computer Science, AI, Data Science, or related technical field from a top university Familiarity with frameworks More ❯

production-grade LLM applications on Azure. You’ll work on AI-enabled and augmented intelligence solutions such as retrieval-augmented generation (RAG), agentic workflows, and model integrations with a strong emphasis on reliability, performance, security, and continuous improvement. Main Duties and Responsibilities Data & Retrieval Build robust ingestion pipelines for PDFs …/Word/Excel/Audio/JSON and semi-structured sources. Design RAG systems : chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search , pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and … Vault , private networking. Add observability : tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts. Apply evaluation & QA : regression suites, offline eval sets/golden data, RAG evals (faithfulness, answer relevance, citation correctness), A/B tests, win-rate testing. Ensure reliability : rate-limit handling, retries/backoff, idempotency, circuit breakers, caching (e.g., Redis/semantic cache More ❯

innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with … consumer-focused platforms is desirable. - Keen awareness of AI/ML industry trends and best practices. If you’re a hands-on AI engineer looking to shape next-generation research platforms, please send your CV and a brief introduction today. Important: This role does not offer visa sponsorship; applicants must have the right to work in the UK. More ❯

innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with … consumer-focused platforms is desirable. - Keen awareness of AI/ML industry trends and best practices. If you’re a hands-on AI engineer looking to shape next-generation research platforms, please send your CV and a brief introduction today. Important: This role does not offer visa sponsorship; applicants must have the right to work in the UK. More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Date: ASAP About the Opportunity: We are seeking a highly capable and intellectually curious Junior AI Engineer/Developer to join a fast-growing fintech company building next-generation AI infrastructure for financial services. This role is designed for a recent AI-focused Master’s graduate from a leading university who wants to move beyond academic models and … and capital-markets workflows into well-scoped AI problems and measurable targets Contributing to internal R&D on LLM evaluation, retrieval-augmented generation (RAG), and methods for improving reliability and explainability of models in financial contexts What We’re Looking For: A recently completed AI-focused Master’s degree from a top-tier university … tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building simple RAG or prompt-based systems) is highly advantageous Comfortable working in Linux-based development environments, using Git, testing, and basic CI practices A structured, “extended thinking” mindset: you enjoy breaking down More ❯

Date: ASAP About the Opportunity: We are seeking a highly capable and intellectually curious Junior AI Engineer/Developer to join a fast-growing fintech company building next-generation AI infrastructure for financial services. This role is designed for a recent AI-focused Master’s graduate from a leading university who wants to move beyond academic models and … and capital-markets workflows into well-scoped AI problems and measurable targets Contributing to internal R&D on LLM evaluation, retrieval-augmented generation (RAG), and methods for improving reliability and explainability of models in financial contexts What We’re Looking For: A recently completed AI-focused Master’s degree from a top-tier university … tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building simple RAG or prompt-based systems) is highly advantageous Comfortable working in Linux-based development environments, using Git, testing, and basic CI practices A structured, “extended thinking” mindset: you enjoy breaking down More ❯

of OWASP Top 10 and a proactive approach to identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. More ❯

of OWASP Top 10 and a proactive approach to identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. More ❯

as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware pipelines to maximize model accuracy and relevance. Integration: Seamlessly integrate deployed AI models with existing enterprise systems, APIs, and data stores using back-end languages like Python … Data Engineering for Generative AI: Experience in preparing and curating diverse training datasets (structured/unstructured text, images, code). Deep knowledge of data preprocessing, tokenization, and embedding generation techniques. Hands-on experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Stakeholder & Strategic Partnership: Ability to partner effectively with business More ❯

as advanced chatbots, summarization tools, document Q&A systems, and code assistants. Advanced Techniques: Apply sophisticated techniques like Prompt Engineering , Retrieval-Augmented Generation (RAG) , and context-aware pipelines to maximize model accuracy and relevance. Integration: Seamlessly integrate deployed AI models with existing enterprise systems, APIs, and data stores using back-end languages like Python … Data Engineering for Generative AI: Experience in preparing and curating diverse training datasets (structured/unstructured text, images, code). Deep knowledge of data preprocessing, tokenization, and embedding generation techniques. Hands-on experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Stakeholder & Strategic Partnership: Ability to partner effectively with business More ❯

A leading multi-strategy investment firm is seeking a Senior AI Engineer to join a high-impact Applied AI team focused on building next-generation tools that enhance decision-making across the investment lifecycle. Operating at the intersection of finance and machine intelligence, the team is responsible for developing production-grade AI systems that empower portfolio managers, analysts … containerised environments (Docker, Kubernetes). Solid grasp of distributed systems, networking, and infrastructure-as-code practices. Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM integration is a plus. Exposure to cloud platforms (AWS preferred) and messaging systems (Kafka, RabbitMQ) is advantageous. Strong communication skills and the ability to work across technical and More ❯

a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI More ❯

a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience with retrieval-augmented generation (RAG) or foundation models Exposure to NLP, recommendation systems, or time series forecasting Familiarity with streaming architectures and experimentation platforms Understanding of healthcare data standards (HIPAA, FHIR) Interest in ethical AI More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

have immediate, visible impact. 🔧 What You’ll Be Doing Designing secure, scalable APIs in Python/FastAPI Building and optimising Retrieval-Augmented Generation (RAG) pipelines Owning vector databases (pgvector, Weaviate, FAISS) and embedding strategies Integrating OpenAI/Bedrock models and developing guardrails & evaluation flows Ingesting and structuring data for high-performance retrieval … the founders to set the product and technical roadmap 💡 What You’ll Bring 5+ years’ full-stack experience with Python + React/Next.js Proven hands-on AI engineering — RAG systems, embeddings, hybrid search Solid cloud & data skills (AWS, SQL/NoSQL, containerisation) Familiarity with LangChain/LlamaIndex and LLM evaluation tools a bonus Start-up mindset — proactive, hands-on More ❯

root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product More ❯

root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯