17 of 17 Remote/Hybrid Retrieval-Augmented Generation Jobs in Central London

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 ...

hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across … client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks ...

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 ...

Responsibilities Design & Deliver: Architect and implement cloud and AI-ready solutions on Azure, building repeatable patterns and integration services that support next-generation workloads. Secure AI Architecture: Develop and scale secure infrastructure architectures that allow applications to safely access both cloud-based backend services and on-premises data … Beyond the Basics): Real-world enterprise experience designing and deploying solutions centred around agentic workflows, Retrieval-Augmented Generation (RAG), and vectorisation patterns, rather than purely self-taught or personal interest projects. Software Engineering & Tech Stack: High proficiency in Python and PowerShell for building automation ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Python and FastAPI on the backend, React and TypeScript on the frontend, Postgres, ElasticSearch and vector databases for data, and LLMs, agents and RAG across the AI layer. What they're looking for Has built and managed an engineering team through a high-growth scaling phase, not just inherited ...

enterprise clients. We work with organisations to understand their workflows, identify where AI can automate or augment work, and build practical systems across LLMs, RAG, workflow automation, document intelligence, operational copilots, data extraction, and enterprise integrations. Our projects move quickly, so delivery is critical. We need someone who can help ...

reusable agent components and playbooks Proactively surface new automation opportunities across the business Key Skills Python & LLM agent frameworks (LangChain, CrewAI, LlamaIndex) Prompt engineering & RAG pipelines Business analysis & stakeholder management Process mapping & workshop facilitation Microsoft 365 & Microsoft Copilot No-code/low-code tooling (Zapier, Make) Desirable Skills Experience … etc. Strong enough technically to assess feasibility and scope what is buildable; commercially sharp enough to prioritise what is worth building. Familiarity with LLMs, RAG pipelines, tool/function calling, and integrating AI into real business workflows. Proven ability to lead discovery workshops and translate complex business problems into clear ...