51 to 75 of 80 Retrieval-Augmented Generation Jobs in the UK excluding London

engineering experience in product focused environments A track record of taking features or products from idea to launch Experience building with LLMs including RAG, semantic search and vector stores Hands on with TypeScript, React, Node and Python Comfortable deploying to AWS, GCP or Azure Curious, fast, accountable and motivated ...

Ability to build responsive interfaces and manage complex backend logic. Excellent problem-solving and time management skills. Bonus Skills: Experience with Azure, Docker, LangChain, RAG models, and pandas. What's on Offer Transparent salary framework and twice-yearly promotion opportunities. 25 days annual leave plus three extra days at Christmas. ...

Centre of Excellence within a consultancy or Microsoft Partner environment. Deep expertise in enterprise AI solution design, including generative AI, Azure OpenAI, Copilot Studio, RAG, cognitive services, and data orchestration patterns. Strong background in the Microsoft ecosystem, especially Dynamics 365, Power Platform, and Azure services. Hands‐on experience shaping ...

applications using Copilot Studio (Full), Power Platform, Dynamics 365, and Azure AI; establish security, governance, and performance baselines. Design and implement LLM-powered solutions (RAG, prompt engineering, grounded generation) with data governance, telemetry, and quality monitoring (LLMOps). Integrate Microsoft 365 and Dynamics 365 with enterprise systems ...

storage and search systems (e.g. pgvector, Pinecone, Azure Search), as well as experience working with graph technologies like Neo4j Practical understanding of retrieval-augmented generation pipelines and how to implement structured outputs or link models to graph-based knowledge systems Track record of optimising ...

technical prioritisation across multiple workstreams Building and shipping production features using .NET, Azure, React, and modern AI frameworks Implementing Generative AI capabilities using LLMs, RAG, and agentic approaches Upholding engineering quality through code reviews, testing practices, and technical standards What you’ll bring to the table as a Lead Full ...

Engineer - LLM RAG AWS MLOps – Bristol (Hybrid) I'm working with a fast-growing tech company in Bristol that needs an AI/ML Engineer to build and deploy machine learning and LLM solutions. You'll be working across the full ML lifecycle—from design through to production … doing: Building and deploying ML models and LLM applications Fine-tuning large language models for specific use cases Working with prompt engineering and RAG systems Creating end-to-end ML pipelines—ingestion, feature engineering, deployment Developing LLM-powered tools: chatbots, automation, content generation Implementing MLOps practices: versioning, experiment ...

React.js + Node.js 100% Remote (UK-based only) Desirable Skills Knowledge of SQL or React Experience with AI/LLMs or RAG (Retrieval-Augmented Generation) Familiarity with integration testing Exposure to multiple programming languages beyond TypeScript Daily use of AI coding assistants Strong problem ...

multi-agent collaboration Develop and optimize AI/ML models for performance, scalability, and efficiency Build advanced solutions using LangChain for agent-based and RAG systems Integrate AI capabilities using Google ADK within enterprise-grade cloud environments Stay up to date with the latest advancements in AI/ML technologies … solutions. Your Profile Key skills/knowledge/experience: Hands-on experience with Agentic AI workflows and autonomous agents Advanced proficiency in LangChain and RAG systems Expertise in Google ADK and GCP cloud services Strong programming skills in Python (and optionally R or Java) Extensive experience with AI/ ...

pipelines, and API services Develop sophisticated prompt engineering strategies for LLM-based features, including few-shot learning, chain-of-thought reasoning, and retrieval-augmented generation Optimize models for specific use cases and performance requirements Design and optimize database schemas for relational database Collaborate with ...

architectures, and emerging best practices. What you’ll bring: Expertise in AI and Machine Learning, including agent-based AI, RAG (Retrieval Augmented Generation), multi-agent systems and conversational agents. Strong programming skills in Python, Java or .NET. Experience with GenAI and LLMs (e.g. ChatGPT ...

work on developing & implementing AIML Solutions for Test Automation in the Securities Processing space. This will entail building AIML Solutions for Test Generation, Test Prioritization, Defect Triage/Reporting, Code Coverage, Framework Migration/Setup. The role requires experience in AIML(LLMs, Gen AI & Agentic AI) & Python. … aspects of AIML & Software Development including: Knowledge of AIML & Python is must. Ability to develop and implement Generative AI & Retrieval Augmented Generation solutions focused on software testing. Experience with Large Language Models(GPT, Claude). Hands- on experience with GitHub Copilot. Must ...

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 … 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 ...

create meaningful impact. Key Responsibilities: Design and implement AI workflows and models for performance and scalability. Build solutions using LangChain for agent-based and RAG systems. Optimize and scale AI/ML models for efficiency. Apply prompt engineering techniques to improve AI outputs. Collaborate with cross-functional teams to translate …/ML projects. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Desirable skills/knowledge/experience: Familiarity with LangChain and RAG systems. Experience with public cloud platforms (e.g., Google Cloud, Azure). Knowledge of prompt engineering techniques. Exposure to multi-agent orchestration frameworks. Understanding of ethical ...

Face APIs) into internal tools and customer-facing applications. Design and implement workflows powered by AI, such as content summarization, support automation, documentation generation, or intelligent query handling. Develop prompt chains and prompt strategies for specific business functions (engineering assistance, product support, operational efficiency). Collaborate with cross … search tools. Experience building internal tooling or developer productivity enhancements using AI. Exposure to customer support AI tools or RAG (retrieval augmented generation) systems. Why Join Paydock? Work with a passionate, remote-first team that's reshaping payments. Opportunity to lead and define ...

User-Defined Agent Logic: Creating a \"no-code\" engine where users can verbally define workflows and guardrails that the system executes deterministically. Hierarchical & Auditable RAG: Routing queries through complex layers of patient history, clinical guidelines, and organizational policies with full traceability. Resilient Orchestration: Managing long-running conversation states, tool usage … executor patterns and manage shared memory across agents. Prompt Engineering & Optimization: utilize programmatic approaches to compile and iteratively improve prompts based on evaluation metrics. RAG Optimization: Enhance retrieval signal through hybrid search, re-ranking, and query rewriting, ensuring high context precision and recall. Observability & Evals: Build robust tracing ...

presentations, advisory roles. Preferred: Educated to at least degree level in AI, Computer Science, or related field. Experience with PyTorch/TensorFlow, vector databases, RAG, and orchestration tools. Background in start-ups (hands-on generalist) or consultancies (client-facing). Exposure to regulated industries. Independent, entrepreneurial mindset; comfortable working with … ecosystem. Culture: Join a fast-moving team operating at the frontier of applied AI. Agentic AI, Multi-Agent Systems, LLM Deployment, LangGraph, LangChain, RAG, AI Orchestration, AI Consultant, Software Engineering for AI, AI Productionisation, Autonomous AI Systems, AI Architect, AI Careers, AI Jobs Remote. ...

additional AI Engineer join the existing team on a expanding project. This role will be shipping production-grade GenAI features (e.g., retrieval-augmented generation, assistants, summarisation) that are safe, reliable, and measurable. This role is based in a Local office. This role will … guardrail incidents, drift, telemetry dashboards Required Skills & Experience: Python for application glue; Fast API for inference/middleware services. LLM integration patterns (prompt engineering, RAG, tool-use/agents, function calling). Evaluation & safety: automated prompt/response evals, LLM-as-a-judge, red-teaming, content filters, guardrails. LLMOps practices ...

orchestration, prompt frameworks, and evaluation loops Build multi-agent systems (planning, tool use, safety constraints, monitoring) Implement retrieval and vector-based architectures (RAG, embeddings, semantic workflows) Apply ontology and knowledge-modelling concepts for more precise reasoning Integrate APIs, tools, and enterprise systems Set the technical direction for your … practices Influence internal standards and architectures Experience Needed 6–8+ years in software, AI, or applied data engineering Strong hands-on experience with LLMs, RAG, vector stores, and embeddings Experience building or orchestrating multi-agent systems Strong Python skills and ability to ship production-grade code Experience with at least ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … Langchain, AutoML, OCR, STT, feature stores, vector DB. Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using cloud-based solutions (networking, security, storage, monitoring, scaling, DR/HA) on one or more cloud platforms SW Engineering ...

automation across critical UK sectors. 🤖 Data Scientist You’ll develop end-to-end ML and Generative AI solutions, including chat-based applications, RAG pipelines, and LLM-powered tools using Azure Machine Learning, Azure OpenAI, and vector databases. Why Join? You’ll work at the edge of innovation, building solutions that … combine: Azure’s evolving data ecosystem (ADF, Synapse, Databricks, Fabric) Generative AI + LLM integration (Azure OpenAI, LangChain, RAG) Real-world impact across nationally important infrastructure A collaborative, values-driven team culture We’re looking for people with a builder’s mindset — analytical, curious, and eager to explore where ...

extremely experienced Head of Backend and VP of engineering as well as closing working with a team of doctors helping build the next generation of AI powered clinical knowledge tools As a Senior Backend Engineer, you'll play a key role in building and scaling the core infrastructure … build robust, scalable cloud-first backend systems. Contribute to infrastructure-as-code practices and DevOps tooling. Build and maintain LLM-powered features such as RAG pipelines for clinical information. Develop and optimise agentic document extraction workflows to process clinical PDFs, policies, and handbooks into structured formats. Collaborate closely with ...

AIML, Machine Learning & Data Science. Large Language Models(GPT, Claude), Generative AI, Retrieval Augmented Generation. Agentic AI, CoPilot, MCPs. AIML Algorithms(Regression, Classification, Decision Trees, KNN, K-Means) Python (NLTK, NumPy ...

AIML, Machine Learning & Data Science. Large Language Models(GPT, Claude), Generative AI, Retrieval Augmented Generation. Agentic AI, CoPilot, MCPs. AIML Algorithms(Regression, Classification, Decision Trees, KNN, K-Means) Python (NLTK, NumPy ...

graph population Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link prediction, anomaly detection) Optimize graph performance, scaling, and query efficiency Liaise with client stakeholders … Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.) Strong background in pipelines, ETL, and entity resolution Exposure to integrating KG + LLM or RAG architectures Experience with graph algorithms, embeddings, or GNNs Cloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD) Excellent communication skills — able ...