101 to 125 of 304 Retrieval-Augmented Generation Jobs in the UK

Youll work at the intersection of: AI strategy Solution architecture Hands-on delivery What youll be doing: Architecture & Delivery Design and scale Generative AI, RAG, and Agentic systems in production Build enterprise AI platforms across AWS/Azure/GCP Select LLMs, vector databases, and orchestration frameworks Ensure solutions … youll need (must-have): Experience as an AI Architect/ML Architect/GenAI Architect Strong expertise in: Generative AI & LLMs, RAG (Retrieval-Augmented Generation), Agentic AI frameworks Hands-on with; LLMs (OpenAI, Llama, Claude, Mistral), Vector DBs (Pinecone, Weaviate, FAISS), Frameworks (LangChain, LlamaIndex ...

/ML and GenAI at enterprise scale — real impact, not just prototypes Expert Python with hands-on experience in PyTorch, TensorFlow, LangChain, LangGraph, RAG pipelines, and LLMs Solid MLOps/LLMOps fundamentals: CI/CD for ML, model governance, and evaluation frameworks Broad cloud experience across AWS, Azure ...

Regulatory compliance automation Document intelligence (KYC, contracts, trade docs) Customer insights & conversational AI You will work on cutting-edge technologies including LLMs, vector databases, RAG architectures, and cloud-native data platforms, helping organizations unlock value from structured and unstructured data. Hybrid working: The places that you work from … time. Your Role: Design and build end-to-end Gen AI pipelines using LLMs (Open AI, Azure Open AI, Anthropic) Develop RAG architectures with vector databases (Pinecone, FAISS, Azure AI Search) Optimize LLM outputs using prompt engineering, embeddings, and evaluation techniques Build AI solutions for document processing, compliance, and banking ...

from project start. Solutions may use a wide range of approaches, including agentic systems, model context protocol (MCP) servers, retrieval augmented generation (RAG), classical machine learning, knowledge graphs, data transformations, and business logic. The emphasis is on solving the right problem rather than using … data science libraries such as pandas, scikit-learn, LangChain, etc. • Experience with LLMs, including foundation model APIs, prompt engineering, and retrieval augmented generation • Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, and Deep Learning ...

systems, software engineering, and cloud infrastructure. Key Responsibilities: Core Duties Design, implement, and maintain AI agent workflows, including retrieval‐augmented generation (RAG), orchestration, tool/function invocation, and policy‐based routing Build cloud‐native backend services and APIs to support AI‐driven applications … engineering experience with ownership of production systems 3+ years of hands‐on experience building and deploying AI/LLM‐based systems in production (agents, RAG pipelines, orchestration) Strong experience designing and delivering cloud‐native systems, including APIs, microservices, containers, and serverless or event‐driven architectures Proficiency in Python, Java ...

Linked Data. Experience with graph databases or triple stores such as GraphDB, Stardog, Neo4j, Amazon Neptune, or Blazegraph. Experience with embeddings, vector databases, RAG, LLM-based enrichment, or knowledge graph completion. Experience with MLOps tools such as Docker, Kubernetes, MLflow, Weights & Biases, Airflow, or similar. Experience with ...

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 ...

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 ...

datastores AI & Automation Hands-on experience integrating LLMs, AI APIs (OpenAI, Azure OpenAI, etc.), or ML models into production applications Familiarity with agentic frameworks, RAG pipelines, or AI-assisted workflow automation Ability to assess where AI genuinely adds value and communicate that clearly to non-technical stakeholders Mindset & Adaptability Proven ...

Comfortable using modern AI-assisted engineering workflows, including agentic coding tools and LLM-based automation. Familiarity with concepts such as MCP servers, tool-calling, RAG/vector search, embeddings, and AI-assisted platform operations. Working knowledge of databases and data platforms, including SQL databases such as PostgreSQL/MySQL ...

Required Experience Strong programming skills, particularly in Python Experience with machine learning and AI, including LLMs or related technologies Knowledge of areas such as RAG architectures, agent-based AI, computer vision, or audio processing Experience working with cloud platforms (AWS or Azure preferred) Familiarity with Docker, Linux/Unix environments ...

Required Experience Strong programming skills, particularly in Python Experience with machine learning and AI, including LLMs or related technologies Knowledge of areas such as RAG architectures, agent-based AI, computer vision, or audio processing Experience working with cloud platforms (AWS or Azure preferred) Familiarity with Docker, Linux/Unix environments ...

technical teams or senior specialists in high stakes modelling environments/li , li Deep understanding of AI/ML systems including LLMs, agentic architectures, RAG pipelines, credit or pricing models, or risk modelling techniques/li , li Hands-on experience developing or validating models, performing statistical testing, and analysing model ...

delivering a modern enterprise data platform. This opportunity offers the chance to work on large-scale data initiatives, modern cloud technologies and next-generation analytics capabilities that will support strategic decision-making across the business. The Opportunity You will join a growing data function responsible for building … environments Desirable Experience Microsoft Fabric Power BI development PySpark REST API integrations Lakehouse architectures AI and Machine Learning platforms Retrieval Augmented Generation (RAG) Vector databases Generative AI solutions Power Platform technologies Data transformation or modernisation programmes What We're Looking For We're looking ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents) Experience translating research and experimentation into production systems Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management Hands-on experience ...

Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents) Experience translating research and experimentation into production systems Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management Hands-on experience ...

EventBridge, SQS, Step Functions Databases: DynamoDB, PostgreSQL, Aurora, MongoDB Frontend: React, TypeScript, MUI DevOps: AWS CDK, Terraform, Docker, GitLab CI, CodePipeline AI: Amazon Bedrock, RAG, LLM integrations Skills Required Commercial software engineering experience Strong AWS cloud/serverless experience Strong backend development skills in TypeScript, Python, or Go CI/ ...

technical delivery — from requirements gathering through to deployment and ongoing support Hands-on experience with AI/LLM integration (OpenAI, Azure OpenAI), RAG pipelines, or agentic frameworks is a key requirement Will provide technical leadership and mentoring to junior engineers and actively participate in architecture discussions and code reviews Must ...