1 to 25 of 79 Retrieval-Augmented Generation Jobs in London

organization. The team designs, develops, and supports enterprise-grade AI applications, including Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI solutions. Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those … success criteria for AI initiatives. Design, develop, and deliver scalable AI solutions, including Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent automation capabilities aligned to business objectives. Evaluate technology, model, and platform options, providing recommendations based on business value, cost, risk, strategic ...

develop and evaluate AI-powered proof-of-concepts that demonstrate how Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI assistants and agentic AI technologies can improve operational efficiency, automate investigative tasks and support security analysts. What You'll Be Doing Designing and building … security operations. Creating AI assistants, copilots and agent-based workflows to enhance analyst productivity. Implementing Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources. Applying prompt engineering techniques to optimise AI performance and accuracy. Integrating AI capabilities with SIEM, SOAR and other cyber security ...

enterprise standards. Design enterprise-scale AI architectures covering agent orchestration, large language models (LLMs), retrieval-augmented generation (RAG), knowledge management, integrations, governance, security, and observability. Assess client technology landscapes, data estates, cloud platforms, and security frameworks to establish the foundations required for successful … focused organizations. Technical Knowledge Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and AI application architectures. Knowledge of cloud platforms including Microsoft Azure, AWS, and Google Cloud. Experience with modern data platforms including Databricks ...

agentic AI. Continuous Learning: Stay updated with the latest trends in the AI engineering field, such as the modern AI stack, synthetic data generation, and Explainable AI. … Skills/Experience: Engineering Foundations: Strong proficiency in Python and robust software engineering principles, with experience operating as part of engineering teams. Generative AI & RAG: Proven experience working with LLMs and designing Retrieval-Augmented Generation (RAG) architectures, including knowledge of semantic search and vector ...

PyTorch FastAPI Knowledge Graphs Kubernetes Docker Infrastructure as Code MLOps Event-Driven Architecture Vector Databases Retrieval-Augmented Generation (RAG) Technology Stack Python SQL FastAPI PyTorch Docker Kubernetes AWS Azure Git CI/CD Knowledge Graphs AI/Large Language Models (LLMs) Amazon Bedrock Azure ...

standards across AI projects. Design and deliver solutions involving generative AI, large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering and agentic AI. Establish robust approaches to model evaluation, monitoring, performance measurement and continuous improvement. Drive high-quality engineering practices, including Python development … machine learning solutions into production. Strong technical leadership and architecture experience across AI engineering and software delivery. Practical knowledge of generative AI, LLMs, RAG, prompt engineering, agentic AI and model evaluation. Strong Python development skills and a sound understanding of software engineering best practice. Experience delivering AI solutions at scale ...

public sector and commercial experience Successful academic background in your specialist discipline Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and other patterns used to support Generative AI solutions on platforms such as Amazon Bedrock. Experience developing data-based apps in Streamlit/ ...

world impact. This position sits within a growing AI function and will focus heavily on Retrieval-Augmented Generation (RAG), agentic workflows, evaluation frameworks, and LLM optimisation. Key Responsibilities: Design and develop scalable RAG pipelines and generative AI workflows Build solutions using LangChain, LangGraph … contribute to technical best practices Key Requirements: Strong Python engineering experience Commercial experience building production-grade AI/ML systems Hands-on experience with RAG architectures and LLM workflows Experience with LangChain, LangGraph, and/or Llama Index Understanding of evaluation methodologies for generative AI Experience working within scalable cloud ...

cloud technology. You'll take ownership of AI architecture and implementation, designing multi-agent workflows, retrieval-augmented generation (RAG) solutions and AI microservices. Working closely with architects and product teams, you'll turn business requirements into secure, reliable AI applications, with a focus … Python development skills Azure OpenAI and Azure AI Foundry Semantic Kernel and LangGraph Model Context Protocol (MCP) and tool integration Azure AI Search and RAG architecture Multi-agent systems and orchestration workflows Vector databases, embeddings and semantic search Event-driven architectures and REST APIs Docker, Kubernetes and AI microservices MLOps ...

agent-based patterns, workflow orchestration and enterprise AI integration. Practical experience applying techniques such as retrieval-augmented generation (RAG), knowledge grounding, prompt engineering and human-in-the-loop design patterns. Experience designing secure and controlled AI solutions, including guardrails, responsible AI, explainability and governance ...

machine learning, Generative AI and prompt engineering. Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI evaluation approaches. Strong data analysis, visualisation and statistical modelling skills. Experience managing AI experimentation and model evaluation activities. Understanding of Responsible AI principles ...

shipping AI-powered products end-to-end using LLM technologies. Owning and scaling the retrieval-augmented generation (RAG) and AI application layer. Developing secure, production-grade systems including guardrails, evaluation frameworks, monitoring, caching, and token cost optimisation. Working across the stack, including backend services ...

. Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions. Preferred qualifications: Masters degree or PhD in Artificial Intelligence, Computer Science, or a related ...

automated resolution rates. Working knowledge of REST APIs, JSON payloads and integration troubleshooting. Understanding of Retrieval-Augmented Generation (RAG), knowledge base structure, content quality and AI grounding. Ability to work closely with business analysts to translate requirements into effective Intercom configurations. Confidence challenging unnecessary ...

experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ...

organisations from identifying opportunities through to enterprise adoption and measurable business impact. Strong understanding of Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, with awareness of major enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience … Strategy Director, Enterprise AI Consultant, AI Consulting Lead, Data & AI Strategy Consultant, Generative AI, GenAI, Agentic AI, AI Agents, RAG, Retrieval Augmented Generation, Decision Intelligence, Intelligent Automation, AI Operating Models, AI Architecture, Data Platforms, Semantic Layers, Data Products, Responsible AI, AI Governance, Cloud Data ...

solutions. You will help clients translate business challenges into scalable AI architectures, leveraging Agentic AI, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and modern cloud technologies. The places that you work from day to day will vary according to your role, your needs … home 100% of the time. Your Role Design and develop enterprise AI solutions, with a particular focus on Agentic AI, Generative AI, and RAG architectures. Work with clients to understand business requirements and translate them into scalable technical solution designs. Build, integrate, and optimize AI applications using Python and leading ...

track record delivering enterprise-scale AI/ML solutions into production Strong experience leading technical teams and complex transformation programmes Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms ...

decisions and mentoring other engineers. Desirable: Python, FastAPI, LangGraph, LangChain or similar AI frameworks. JSON-RPC, SSE, WebSockets and event-driven architectures. Experience with RAG, LLM function calling and context management. An interest in sport and the sports betting industry. Why Consider This Opportunity? This is an opportunity to take ...

Actions, Azure DevOps, RBAC and cost controls. Solid software engineering fundamentals: Clean Code (SOLID, DRY), DDD, modular architecture, TDD and code quality tooling. Desirable: RAG pipelines, MCP, LLM integration (OpenAI, Gemini, Hugging Face models), LangSmith, TruLens, and agentic frameworks such as LangChain, CrewAI, Autogen, OpenAI Agents and Google ADK. … React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents SDK, Google ADK, RAG, retrieval augmented generation, MCP, LangSmith, TruLens, prompt engineering, Docker, Kubernetes, AKS, GCP, Azure DevOps, GitHub Actions, PostgreSQL, BigQuery, TDD, DDD. Deerfoot Recruitment Solutions ...

design and development of AI, Machine Learning, and Generative AI solutions. Drive the adoption of Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and Agentic AI approaches. Define evaluation frameworks, testing strategies, and model performance standards. Act as the technical authority for scientific decisions … What We're Looking For Significant hands-on experience in AI, Machine Learning, and Data Science. Deep expertise with LLMs, Generative AI, Prompt Engineering, RAG, and Agentic Systems. Strong Python programming skills and experience with modern AI frameworks. Excellent understanding of statistics, machine learning methodologies, and model evaluation. Experience delivering ...

MORELA AI & Engineering Recruitment Data Engineer (RAG & Retrieval) 2-year contract | Central London | Active SC | Outside IR35 Morela is supporting a specialist technology consultancy on a 2-year Data Engineer contract in Central London, delivering on a UK government programme. Outside IR35, rate TBC. We need a genuinely … strong all-round data engineer first and foremost, with recent hands-on RAG experience on top. Active SC is essential - eligibility will not be considered. About the Client A specialist technology consultancy embedding engineers into SC-cleared government delivery teams. They focus on long-term programme work and give their ...

frameworks, risk assessments, policies and controls. Practical understanding of how AI systems are built and secured. Good understanding of LLMs and agentic AI, including RAG, tool use and orchestration. Knowledge of AI security risks including prompt injection, data leakage and excessive agency. Strong understanding of relevant AI regulation and frameworks ...

repeat manual work. Secure AI Application and Cloud-AI Guardrails Define secure design patterns for AI-enabled applications, including LLM-based features, retrieval-augmented generation, AI agents, AI APIs, copilots, and automation workflows. Establish cloud security requirements for AI workloads, including identity, secrets, data … NIST AI Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance. Experience with RAG architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling. Experience building security knowledge assistants, prompt libraries, AI-assisted review workflows ...

enjoy building real solutions. You'll use Python as your primary development language, developing APIs, services and AI applications using technologies such as LLMs, RAG, AI agents and vector search. You'll work across the development lifecycle, helping take GenAI ideas and POC's through to robust, production-ready applications … enterprise clients. What you'll be doing: Build production applications and APIs using Python and FastAPI Develop LLM, RAG and AI agent solutions Build RAG pipelines covering embeddings, retrieval and generation Work with OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar ...