51 to 75 of 161 Retrieval-Augmented Generation Jobs in the UK

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 ...

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 ...

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 ...

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 ...

across an organisation. Data, AI & Intelligent Systems Expertise: Strong understanding of modern AI capabilities, including Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, and enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience shaping enterprise ...

code already in place Requirements - 5+ years as an AI/ML engineer delivering NLP and ML models into production SaaS - Production LLM experience: RAG, fine-tuning, evaluation, monitoring - Strong Python, including building APIs and integrating models into applications - NLP frameworks such as Hugging Face Transformers, PyTorch, spaCy or TensorFlow ...

have experience building and operating scalable production applications with significant user numbers You have practical experience with LLMs and AI application development, including RAG, semantic search, LLMOps or agentic workflows You have an understanding of AI application reliability, evaluation and production monitoring You have experience with AWS and CI/ ...

hands-on experience taking AI systems into production. Key experience includes: Production Python PyTorch, Hugging Face Transformers or similar Strong hands-on LLM experience RAG, vector search, prompting, tool use and agent orchestration Designing and running model evaluations Cloud deployment, containers and CI/CD Understanding AI attack surfaces ...

doing Designing, developing and deploying machine learning models and AI solutions Building predictive, recommendation and optimisation capabilities Developing Generative AI solutions, including RAG architectures and agent-based frameworks Creating and maintaining data pipelines, feature stores and training datasets Implementing MLOps practices and model lifecycle management Monitoring model performance, drift ...

Azure, including SaaS and PaaS offerings. Hands-on experience building and deploying with modern AI, including large language models and agentic AI (prompt engineering, RAG, tool and function calling, orchestration), on the Microsoft AI stack such as Azure OpenAI, Azure AI Foundry and Azure AI services. Proven experience of technical ...

deliver GenAI and Agentic AI products. The individual must have hands-on experience developing production-grade GenAI/Agentic AI solutions using LLMs, RAG and agentic workflow technologies. The role requires strong Python software engineering skills alongside practical experience designing reliable, secure and maintainable AI-enabled applications. Key responsibilities include … including prompt engineering, structured outputs, context management, model configuration and validation of model responses. RAG & Knowledge Retrieval: Design and implement Retrieval-Augmented Generation solutions, including document ingestion, parsing and chunking, embeddings, indexing, semantic/hybrid search, filtering, reranking and evidence grounding. ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

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 ...

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 ...

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 ...

security. The confidence to take ownership of projects, challenge ideas constructively and explain technical decisions to non-technical colleagues. Experience with LLMs, AI agents, RAG, vector databases or workflow automation tools would be useful, but you don't need to have worked with every technology. Why consider it? The business ...

fundamentally change how analysts work and how Fitch operates Drive breakthrough AI innovation and experimentation boldly – Lead exploration of generative AI, multi-agent systems, RAG architectures, model fine-tuning, prompt engineering, and other emerging ML technologies; create cutting-edge proofs-of-concept; evaluate what's transformative versus what's hype … environments Advanced generative AI expertise – Extensive hands-on experience developing and integrating generative AI solutions, working with large language models, building agentic systems, implementing RAG architectures, and training/fine-tuning neural networks using frameworks like PyTorch Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics ...

fundamentally change how analysts work and how Fitch operates Drive breakthrough AI innovation and experimentation boldly – Lead exploration of generative AI, multi-agent systems, RAG architectures, model fine-tuning, prompt engineering, and other emerging ML technologies; create cutting-edge proofs-of-concept; evaluate what's transformative versus what's hype … environments Advanced generative AI expertise – Extensive hands-on experience developing and integrating generative AI solutions, working with large language models, building agentic systems, implementing RAG architectures, and training/fine-tuning neural networks using frameworks like PyTorch Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics ...

LLMs (local/self-hosted) SignalR real-time communication experience OOP and Entity Frameworks Dependency injection PostgreSQL/SQL Servers/Vector Search/RAG API integration experience AI tools - Claude Code or GitHub Copilot Hands-on experience using OpenAI or Anthropic Highly desirable: Python AI tooling and evaluation scripts ...

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key ResponsibilitiesHands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating ...

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than ...

robust error handling. Build MCP clients and servers that connect agents securely to repositories, enterprise data sources, development tools and business systems. Implement RAG and context-engineering solutions using structured and unstructured data, embeddings, vector search and knowledge stores. Use Claude Code and AI-assisted engineering practices across requirements, coding … control and CI/CD workflows. MCP client/server development or comparable secure tool-integration patterns for agentic applications. Agent orchestration, tool calling, RAG, context engineering, vector databases, event-driven integration and human approval workflows. Deployment through Anthropic APIs and/or Amazon Bedrock or Google Cloud Vertex ...