1 to 25 of 60 Remote/Hybrid Retrieval-Augmented Generation Jobs in the UK excluding London

enterprise-scale AI projects, leveraging the latest Generative AI technologies including LLMs, Agentic AI and Retrieval-Augmented Generation (RAG), while collaborating with data scientists, engineers and senior business stakeholders. The Role As an AI Engineer, you'll take ownership of designing and delivering … Doing Designing and developing enterprise AI and Machine Learning solutions Building Agentic AI frameworks and Retrieval-Augmented Generation (RAG) applications Developing intelligent reporting, recommendation and forecasting solutions Working with Large Language Models (LLMs) and foundation models Deploying production-ready machine learning models into cloud ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions. Tech environment Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure. What we're looking for Proven enterprise AI or ML architecture design, strong cloud ...

with big data technologies (e.g. Hadoop, Hive, Spark). Experience with generative AI, LLMs, or retrieval-augmented generation (RAG). Exposure to Agentic AI concepts, including autonomous agents, tool use, and orchestration frameworks. Experience applying machine learning and AI to scientific ...

Responsibilities Architectural Leadership & Integration Design and implement enterprise-grade AI platforms - including semantic search, Retrieval-Augmented Generation (RAG), and broader generative AI/agentic capabilities - integrating cleanly with the department's complex Legacy and multi-cloud environments. Responsible AI Governance Embed … team. Alongside the DDaT competencies, given the scale of this programme, hands-on depth across the modern AI engineering stack is essential, not just RAG in isolation: Semantic search, vector/embedding infrastructure, and retrieval architecture design LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling ...

enterprise environment. Driving build versus buy evaluations and recommending appropriate technologies. Delivering solutions including retrieval-augmented generation (RAG), agentic AI, automation, and intelligent decision-support tools. Working closely with engineering, security, governance, and business stakeholders. Navigating complex and ambiguous problem spaces to identify practical … fundamentals and experience building scalable applications. Experience making architecture and technology decisions within enterprise organisations. Strong knowledge of modern AI engineering practices, including LLMs, RAG, agentic workflows, and MLOps concepts. Experience working with cloud platforms, ideally AWS. Ability to balance innovation with risk, governance, and operational requirements. Strong stakeholder management ...

solution approaches across the modern AI stack, including Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases and MLOps. Support clients in navigating cloud, security, data governance and operating model considerations required for enterprise AI adoption. Communicate complex machine learning ...

modern AI technologies and concepts, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases AI Solution Architecture MLOps Principles AI Governance and Risk Considerations Candidates are not expected to be hands-on developers but should be capable ...

responsible for: Designing and developing AI agents using modern LLM frameworks Building Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources Developing and deploying Machine Learning models for intelligent decision-making Integrating AI services with enterprise APIs and data platforms Engineering prompts, tool calling ...

understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such ...

understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such ...

agentic workflow frameworks Evaluation harnesses, evaluation datasets and automated test suites for AI outputs Retrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable) LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable) Technical and Professional Expertise Strong software engineering background ...

services Contribute to the development and evolution of a production-grade AI platform Build and integrate AI-powered features such as LLM-driven services, RAG pipelines, and agent-based workflows into core systems Leverage tools like GitHub Copilot, Claude Code, Cursor, or similar AI-assisted engineering workflows. Apply modern software … Desirable: Experience integrating AI into production systems (e.g. chat interfaces, automation, intelligent search) Familiarity with Retrieval-Augmented Generation (RAG), vector databases, or embeddings Experience with cloud platforms (AWS preferred) Awareness of emerging AI tooling (e.g. MCP, A2A, Threads or similar) Open-source contributions ...

multi‐modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval‐Augmented Generation (RAG), APIs, and enterprise data integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability … within agile delivery environments Bonus Points For Experience building AI agent frameworks or autonomous orchestration platforms Knowledge of vector databases, semantic search, and advanced RAG architectures Experience with cloud platforms such as AWS, Azure, or GCP for AI workloads Familiarity with financial services, banking, or regulated enterprise environments Exposure ...

across the organisation. Responsibilities Technical Leadership & Engineering Design Agentic Systems: Design and scale robust, secure, and production‐ready multi‐agent workflows, orchestrations, and advanced RAG architectures, in collaboration with Enterprise Architecture principles. Drive delivery by designing and building agentic solutions, spanning from piloting to full implementation. Define Engineering Excellence: Establish ...

evolve and pragmatic decision-making is essential. Nice to Have Familiarity with vector databases and Retrieval-Augmented Generation (RAG) architectures. Experience working with containerised applications and modern CI/CD pipelines. AWS certifications, including Solutions Architect or Machine Learning Specialty. ...

evolve and pragmatic decision-making is essential. Nice to Have Familiarity with vector databases and Retrieval-Augmented Generation (RAG) architectures. Experience working with containerised applications and modern CI/CD pipelines. AWS certifications, including Solutions Architect or Machine Learning Specialty. ...

providers AI coding tools: GitHub Copilot, Cursor or equivalents Prompt engineering and context design patterns Retrieval-augmented generation (RAG), vector search, embeddings (desirable) Evaluation frameworks and automated quality pipelines for AI outputs Technical and Professional Expertise Solid production experience with C# .NET, including working ...

providers AI coding tools: GitHub Copilot, Cursor or equivalents Prompt engineering and context design patterns Retrieval-augmented generation (RAG), vector search, embeddings (desirable) Evaluation frameworks and automated quality pipelines for AI outputs Technical and Professional Expertise Solid production experience with C# .NET, including working ...

such as LangChain, LangGraph, LlamaIndex, and Hugging Face, including agentic and multi‐step workflows. Proven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems, including vector databases (pgvector, Pinecone, Weaviate, FAISS, etc.) and advanced retrieval strategies (hybrid search, re‐ranking, metadata filtering ...

MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication and stakeholder management skills Ability ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

REST API design and integration Experience with test-driven development and CI/CD workflows Experience integrating AI technologies such as OpenAI, LangChain, or RAG pipelines Understanding of authentication and authorization approaches including OpenID and SAML Experience deploying cloud-native services on AWS with containerized infrastructure and Kubernetes Experience with ...

5+ years experience within software development and AI related rolesStrong experience building GenAI/Applied AI solutionsHands-on with LLMs, AI Agents, Agentic Workflows & RAG Proficiency in Python (TypeScript beneficial)Full-stack development with React, Next.js or SvelteAPI and backend development, including scalable microservicesExperience with SQL, NoSQL and Vector DatabasesCloud ...