726 to 750 of 859 Retrieval-Augmented Generation Jobs in the UK

work includes:* Building and operating LSEG AI Assist, an in‐house agentic experience capable of reasoning, planning, and tool‐calling.* Operating QAS, the enterprise RAG and search layer used to ground agent responses in approved data sources.* Delivering a production Internal MCP Gateway providing discovery, security, policy enforcement, observability … understanding of Model Context Protocol (MCP), including server and tool patterns.* FastAPI and REST API design and implementation experience.* Experience with prompt engineering and RAG‐based architectures.* Containerisation and Kubernetes‐based deployment experience.* Ability to work across platform, product, and governance boundaries in an enterprise environment. Career Stage: ManagerLondon Stock ...

mainly Python across the modern AI engineering stack - harness engineering, skills and tool building, agent workflows and orchestration, agent hosting and sandboxing, guardrails, evals, RAG and context engineering, and tokenomics (cost, latency, model selection). Production-grade LLM system experience is the core requirement. You will work on three types … your primary language. LLM-powered systems in production: real-world experience working with models via APIs - harnesses, orchestration, structured output, tool use and agents, RAG where appropriate. Evals and quality: designing evaluation sets, measuring accuracy, recall and precision for LLM steps, regression-testing prompts and workflows. Safety and guardrails ...

mainly Python across the modern AI engineering stack - harness engineering, skills and tool building, agent workflows and orchestration, agent hosting and sandboxing, guardrails, evals, RAG and context engineering, and tokenomics (cost, latency, model selection). Production-grade LLM system experience is the core requirement. You will work on three types … your primary language. LLM-powered systems in production: real-world experience working with models via APIs - harnesses, orchestration, structured output, tool use and agents, RAG where appropriate. Evals and quality: designing evaluation sets, measuring accuracy, recall and precision for LLM steps, regression-testing prompts and workflows. Safety and guardrails ...

plane for staff and customer authentication. Contribute to AI-enabled quotation and knowledge tools, including human-in-the-loop quote drafting and retrieval-augmented knowledge features. Collaborate closely with mobile, product and engineering colleagues where your APIs are consumed across different surfaces. Take part in architecture … through to delivery. Useful Additional Experience Exposure to React or React Native, particularly where APIs support web or mobile products. Experience with retrieval-augmented generation, vector search or integrating LLM-based features into production products. Experience working in a scale-up, transformation programme ...

plane for staff and customer authentication. Contribute to AI-enabled quotation and knowledge tools, including human-in-the-loop quote drafting and retrieval-augmented knowledge features. Collaborate closely with mobile, product and engineering colleagues where your APIs are consumed across different surfaces. Take part in architecture … through to delivery. Useful Additional Experience Exposure to React or React Native, particularly where APIs support web or mobile products. Experience with retrieval-augmented generation, vector search or integrating LLM-based features into production products. Experience working in a scale-up, transformation programme ...

plane for staff and customer authentication. Contribute to AI-enabled quotation and knowledge tools, including human-in-the-loop quote drafting and retrieval-augmented knowledge features. Collaborate closely with mobile, product and engineering colleagues where your APIs are consumed across different surfaces. Take part in architecture … through to delivery. Useful Additional Experience Exposure to React or React Native, particularly where APIs support web or mobile products. Experience with retrieval-augmented generation, vector search or integrating LLM-based features into production products. Experience working in a scale-up, transformation programme ...

opportunity to advance your career by working with the Global Technology Applied Research (GTAR) center, where your expertise will help develop next-generation solutions for our clients and businesses. We value your creativity, technical skills, and passion for research, offering you a platform to make a real difference. … serving (e.g., test-time compute, speculative decoding, quantization, KV-cache management). Experience in agentic systems (e.g., planning, tool and function calling, retrieval-augmented generation, orchestration). Experience in evaluation and faithfulness (e.g., benchmarks, LLM-as-judge, hallucination and groundedness detection, workflow verification). ...

practices, with the judgement to assess feasibility and shape sound solutions. Comfort with Python, modern LLM and agentic tooling, including model APIs, retrieval-augmented generation, and agents, and SQL/data is expected; hands-on engineering experience is a plus. A bachelor’s degree ...

organization. Shape our generative-AI direction. Own the strategy for applying LLMs and generative AI across the Experiences product — conversational trip planning, retrieval-augmented generation grounded in our first-party reviews and content, and automated content — with rigorous evaluation to control quality and cost ...

continuous delivery pipelines). Requirements Domain & Technical Expertise AI SDLC & LLMOps Fluency: Deep understanding of how AI integrates into modern software engineering—including LLMOps, RAG patterns, Agentic frameworks, fine-tuning vs. prompt engineering, vector storage, and model observability tools. Modern SDLC & Tooling Mastery: Expertise in enterprise DevOps/DevSecOps … responsibilities Delivery & AI Engineering Oversight End-to-End AI SDLC Delivery: Drive the full lifecycle of complex software programmes incorporating AI (Custom LLM solutions, RAG architectures, Agentic Workflows, and AI-powered SDLC tooling) from discovery to production rollout. AI-Assisted SDLC Transformation: Lead initiatives to integrate AI tools (GitHub Copilot ...

scalable application programming interfaces, microservices, and distributed systems Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization Demonstrated ability to own services, components, or features end to end, from technical design through production … from technical design through deployment, monitoring, production support, and continuous improvement Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration Contribute to technical designs, participate in design reviews, and identify risks, constraints ...

scalable application programming interfaces, microservices, and distributed systems Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization Demonstrated ability to own services, components, or features end to end, from technical design through production … from technical design through deployment, monitoring, production support, and continuous improvement Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration Contribute to technical designs, participate in design reviews, and identify risks, constraints ...

code development Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards Apply knowledge of tools within … platform-as-a-service environments, including Kubernetes and Cloud Foundry Familiarity with Generative AI tools and patterns — including prompt engineering, retrieval‐augmented generation, and vector search/embeddings — and safe, secure adoption practices Familiarity with financial services technology environments and enterprise‐grade controls ...

Team" alongside civil servants, implementing the guardrails and standards set by the Lead AI Engineer and Lead Technical Architect. Key Responsibilities Build & Integrate Implement RAG pipelines, prompt templates, and agentic workflows, and wire them into application logic that connects with the department's Legacy and multi-cloud systems. Prompt Engineering … internal government engineers. Required Skills & Experience Practical experience building applications using LLMs or other foundation models, via API or self-hosted Experience with RAG architectures, vector databases, and embedding-based retrieval Solid general-purpose programming (commonly Python) and API design/integration skills Prompt engineering with a systematic ...

enable more reliable and scalable product development Establish end-to-end technical architectures for LLM-enabled systems, covering data pipelines, retrieval/RAG, prompt orchestration and agent workflows to support robust and effective AI implementation Analyse complex constraints across product, data, security, legal and operations, translating them into … services and the supporting platform services required for production delivery AI engineering experience delivering LLM-enabled systems using LLM APIs/Bedrock, including RAG architectures, vector databases and orchestration frameworks DevOps skills including CI/CD pipelines, containerisation and monitoring/observability, with experience defining release and operating practices ...

governance, design standards, and manage risk, non-functional requirements (NFRs), and technical debt. Agentic AI & Commerce Innovation: Design AWS-based agentic AI platforms (orchestration, RAG, memory, guardrails, and MCP). Establish reusable patterns and advise clients on emerging Agentic Commerce standards (ACP, AP2, A2A, and secure payment models). Client … including serverless patterns and appropriate integration components). Agentic AI & Commerce: Strong understanding of building agentic AI platforms on AWS (e.g., Bedrock, orchestrations, RAG, gateways/MCP) and awareness of emerging Agentic Commerce concepts and standards (ACP, AP2, A2A). Software Engineering & API Design: Strong development background (ideally TypeScript/ ...

design and delivery of production-grade Generative AI and AI-powered solutions Owning architecture decisions across AI products and platforms Building and deploying LLM, RAG, and agentic AI systems at enterprise scale Evaluating build versus buy approaches and making pragmatic technology recommendations Working closely with engineering, security, governance, and business … commercial experience delivering Generative AI solutions into production Proven capability leading end-to-end AI projects from discovery through deployment Deep understanding of LLMs, RAG architectures, agentic AI, orchestration, prompting, and evaluation Strong software engineering foundations, including APIs, cloud architectures, and system design Experience making architecture and technology decisions within ...

teams to understand business and technical challenges. Design and develop AI-powered prototypes, proof-of-concepts and product solutions . Apply Generative AI, LLMs, RAG and prompt engineering to real-world use cases. Evaluate and integrate AI platforms, tools, APIs and cloud technologies. Contribute across the full product engineering lifecycle … experience across AI, software development and product engineering . Strong proficiency in Python and JavaScript . Hands-on experience with Generative AI, LLMs and RAG architectures . Experience with prompt engineering and AI APIs/integrations. Experience building prototypes, proof-of-concepts or production-ready solutions. Strong understanding of modern ...

teams to understand business and technical challenges. Design and develop AI-powered prototypes, proof-of-concepts and product solutions . Apply Generative AI, LLMs, RAG and prompt engineering to real-world use cases. Evaluate and integrate AI platforms, tools, APIs and cloud technologies. Contribute across the full product engineering lifecycle … experience across AI, software development and product engineering . Strong proficiency in Python and JavaScript . Hands-on experience with Generative AI, LLMs and RAG architectures . Experience with prompt engineering and AI APIs/integrations. Experience building prototypes, proof-of-concepts or production-ready solutions. Strong understanding of modern ...

concept through to production deployment Designing and developing AI and Machine Learning solutions using Azure and modern AI technologies Building production-ready LLM applications, RAG pipelines and AI agents Working closely with Data Engineering teams to prepare and integrate structured and unstructured data Collaborating with Infrastructure teams to deploy secure … Science and Machine Learning Experience designing and deploying production AI solutions Strong knowledge of AI, Machine Learning and Large Language Models (LLMs) Experience developing RAG solutions and AI agents Excellent Python skills alongside modern AI/ML frameworks and SDKs Experience with Azure AI services or another enterprise AI cloud ...

PrivateLink for cross-cloud data connectivity. AI Readiness : Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. Duties Data Modelling … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for the clients AI product layer. Data Contracts : Partner with Business Analysts to formally define ...

PrivateLink for cross-cloud data connectivity. AI Readiness : Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. Duties Data Modelling … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for the clients AI product layer. Data Contracts : Partner with Business Analysts to formally define ...

PrivateLink for cross-cloud data connectivity. AI Readiness : Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. Duties Data Modelling … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for Bestway's AI product layer. Data Contracts : Partner with Business Analysts to formally define ...

PrivateLink for cross-cloud data connectivity. AI Readiness: Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. DutiesData Modelling Standard … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for Bestway's AI product layer. Data Contracts: Partner with Business Analysts to formally define ...

work includes:\* Building and operating LSEG AI Assist, an in‐house agentic experience capable of reasoning, planning, and tool‐calling.\* Operating QAS, the enterprise RAG and search layer used to ground agent responses in approved data sources.\* Delivering a production Internal MCP Gateway providing discovery, security, policy enforcement, observability … understanding of Model Context Protocol (MCP), including server and tool patterns.\* FastAPI and REST API design and implementation experience.\* Experience with prompt engineering and RAG‐based architectures.\* Containerisation and Kubernetes‐based deployment experience.\* Ability to work across platform, product, and governance boundaries in an enterprise environment.**Career Stage:**Manager**London ...