1 to 25 of 42 Permanent Retrieval-Augmented Generation Jobs in Central London

Senior AI Engineer (Gen AI & RAG) Greater London, England, United Kingdom (On-site) Join an award-winning, internationally recognised B2B Consultancy as a Senior AI Engineer, where you will play a central role in delivering and evolving production-grade generative AI capabilities that power real-world business outcomes. This … intelligence layer of next-generation AI products. You will architect and implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and rigorous evaluation frameworks that ensure AI systems are accurate, reliable, and grounded in genuine business value. Reporting to the Director ...

team is building next-generation AI solutions using Large Language Models, Agentic AI, Retrieval-Augmented Generation (RAG), and intelligent automation to drive measurable business outcomes. Skills & Responsibilities Build and deploy production-grade AI agents and LLM-powered applications. Design agentic workflows using … LangChain, LangGraph, MCP, FastMCP, or similar frameworks. Develop and optimise Retrieval-Augmented Generation (RAG) systems. Integrate AI solutions into products, APIs, and business workflows. Work with AWS, Azure, or GCP to deploy scalable AI systems. Contribute to recommendation, classification, forecasting, and automation initiatives. Strong ...

delivering AI/ML or generative AI systems in production Strong understanding of LLMs , including: Retrieval-Augmented Generation (RAG) Experience building or delivering agentic AI systems Strong Python engineering skills and experience building API-based services Experience with modern data architectures and system design ...

teams to design, develop, and scale production-ready solutions using the latest AI technologies and cloud-native engineering practices. Key Skills: AI & GenAI: LLMs, RAG, Agents, LangChain, LangGraph, CrewAI, Vercel AI SDK, OpenAI, Anthropic, Mistral, Llama. Full Stack Engineering: Python, TypeScript, React, APIs, Microservices, FastAPI. Cloud & DevOps: AWS/Azure … with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...

drive enterprise opportunities from qualification to close. Develop and maintain a strong perspective on how AI – including large language models, agentic architectures, and RAG-based solutions – can drive measurable business value across verticals and functions. Understand customer pain points in adopting and implementing AI solutions, and position Uniphore … trusted partner to address them. Deliver compelling technical presentations and demos showcasing GenAI, Agentic AI, RAG, and LLM-based capabilities tailored to each prospect’s context. Build and deliver custom demos and proof-of-concepts (POCs) to validate business value and technical feasibility. Conduct discovery sessions with key business ...

generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks … skills and solid machine learning fundamentals. Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks. Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact. Familiarity with cloud platforms and modern software engineering practices. Strong ...

implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure ...

focused on developing next-generation agentic AI systems. This is an opportunity to work hands-on with modern AI technologies including LLMs, RAG pipelines, vector databases, and multi-agent workflows while delivering production-grade AI solutions across multiple business domains. What You’ll Do Design and build agentic … well-tested Python code What We’re Looking For 4+ years of experience in Python engineering Hands-on experience with: RAG (Retrieval-Augmented Generation) Agentic workflows Vector databases Experience with LangChain and LangGraph Experience with cloud platforms such as Azure, AWS, or GCP Good ...

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 ...

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 ...

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 ...

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 ...

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 ...

production environments — not just prototypes. Key experience required: • Python and production-grade coding • LLMs, AI Agents & Agentic Workflows • LangChain/LangGraph or similar frameworks • RAG Systems • MCP/FastMCP/FastAPI architectures • Cloud platforms (AWS, Azure, or GCP) • AI system deployment, orchestration & optimisation. This role offers the opportunity to work ...

designing and optimising multi-agent systems for reliability and production performance Understanding of prompt engineering techniques including few-shot learning, chain-of-thought and RAG Familiarity with LLM evaluation strategies and how to measure whether your system is actually working Hands-on with AI orchestration frameworks: LangGraph, LangChain, DSPy ...

Engineering community. What youll bring: A strong understanding of AI, machine learning and agent-based AI concepts, including Retrieval Augmented Generation (RAG), multi-agent systems and conversational agents. Experience developing AI solutions using programming languages such as Python, or similar languages used ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

they’re looking for: Strong experience with Python in a production environment Hands-on experience with LLMs or applied AI (prompt engineering, fine-tuning, RAG, etc.) Experience building APIs and backend services Solid understanding of cloud platforms Ability to work in a fast-paced, product-driven environment Why join? Work ...

into CI/CD pipelines and wider SDLC activities. Should have: Practical exposure to testing AI/ML/LLM‐based systems (e.g. chatbots, RAG applications, AI‐assisted workflows) and an interest in deepening this. Familiarity with approaches to evaluating LLM outputs (for example, semantic‐similarity based methods or using ...

small team, wearing multiple hats, and moving at speed without heavy process. AI/LLM experience (a plus) : Experience building with AI agents, RAG systems, or LLM-powered features is valuable but not required. End-to-end ownership mindset : You've shipped something meaningful on your own—a project, open ...

approach with proven experience or strong hands-on interest in Azure's AI stack, including Azure AI Foundry, Azure OpenAI, AI Search, agents and RAG patterns. Strong practical knowledge of databases, including SQL and NoSQL platforms, schema design, data access patterns, query performance and secure data handling. Ability to design … OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure SQL, Cosmos DB, AKS, storage services and related platform components. Contribute to AI and RAG features, including document ingestion, metadata enrichment, retrieval workflows, grounding, reasoning flows, template generation and agent orchestration. Support Microsoft Fabric and data ...

this Senior Consultant role, you will operate as a hands-on engineer within a squad, designing and implementing AI capabilities such as agents, RAG pipelines and supporting services while ensuring solutions meet enterprise standards for reliability, security and governance. What you'll do Client-facing engineering & delivery Collaborate with client … audiences. Support the adoption of delivered solutions through testing, iteration and feedback cycles. Solution design & implementation Design and implement AI-enabled components such as RAG pipelines, agents and supporting microservices. Integrate solutions with enterprise data sources, APIs and existing platforms while maintaining reliability and security standards. Apply responsible-AI guardrails ...

adaptive AI architectures Implementing prompt engineering at production scale Developing and managing multi-agent workflows Optimising retrieval systems and memory strategies (RAG architectures) Requirements 5+ years commercial experience with Python/PHP Proven experience delivering production-grade AI systems (not just prototypes) Hands-on experience building autonomous systems ...