776 to 800 of 891 Retrieval-Augmented Generation Jobs in England

data estates: quality, lineage, governance, semantic layers, and retrieval frameworks that enable trustworthy AI grounding at scale- Advise on agentic system architecture — RAG, tool-use patterns, memory and state management, multi-agent orchestration, and human-in-the-loop guardrails — with attention to auditability, explainability, and compliance- Collaborate with … into business-aligned recommendations that link data investment to measurable AI outcomes- Develop reference architectures and reusable assets addressing financial services patterns — regulatory-compliant RAG, multi-jurisdictional data mesh, real-time decisioning, and secure agent-to-data connectivity- Publish thought leadership content (whitepapers, blogs, workshops) on data foundations ...

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/ ...

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 ...

real client data during Assess engagements - the prototype is the discovery tool, built while the value case is made * Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) * Iterating in short loops: demoing every few days, taking feedback, changing course without … front-end, back-end and data engineering to build the whole thing yourself * Hands-on production LLM and agent experience: prompt engineering, agent workflows, RAG, tool orchestration and MCP - with evidence you've shipped AI users actually rely on, and how you proved it could be trusted * Evaluation-driven habits ...

real client data during Assess engagements, the prototype is the discovery tool, built while the value case is made Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) Iterating in short loops: demoing every few days, taking feedback, changing course without … front-end, back-end and data engineering to build the whole thing yourself Hands-on production LLM and agent experience: prompt engineering, agent workflows, RAG, tool orchestration and MCP, with evidence you've shipped AI users actually rely on, and how you proved it could be trusted Evaluation-driven habits ...

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 Exchange ...

technical 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 Engagement … 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/JavaScript) coupled ...

Loop and MLOps.Data Architecture Design: You understand and know when to use the following data architecture design patterns RAG (Retrieval-Augmented-Generation), Serverless, DWH models, Data Mesh and Data Products.Hands on mindset: You speak the language of data fluently, whether it's Python ...

DescriptionMajor AccountabilitiesAI Foundations & Reference ArchitecturesDefine reusable architectures, design patterns, and reference implementations for AI systems across Development.Establish common approaches for agentic AI, retrieval-augmented generation, knowledge systems, simulation, digital twins, and human-in-the-loop AI.Provide technical guidance on reuse, extension, and evolution … engineering, or technical architecture initiatives.· Demonstrated experience designing reusable AI architectures, platforms, frameworks, or technical capabilities.· Deep expertise in modern AI systems, including LLMs, RAG, agentic systems, orchestration, and AI lifecycle management.· Experience translating prototypes and local solutions into scalable reusable capabilities.· Experience leading senior technical teams in complex environments. ...

engineering best practicesLeverage 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 standardsApply knowledge of tools within the Software … platforms and platform-as-a-service environments, including Kubernetes and Cloud FoundryFamiliarity with Generative AI tools and patterns such as prompt engineering, retrieval-augmented generation, vector search and embeddings, and safe and secure adoption practicesJ.P. Morgan is a global leader in financial services, providing ...

diagnostic and troubleshooting skills across APIs, logs, and browser-level tooling.Familiarity with AI and LLM-based products — you understand concepts such as retrieval-augmented generation, prompt behaviour, and agentic workflows well enough to triage issues and communicate clearly with both users and engineers.Breadth ...

technology transformation, product leadership or innovation, supported by hands-on delivery experience. Experience with generative and agentic AI, machine learning, predictive analytics, retrieval-augmented generation and enterprise knowledge systems. Knowledge of data architecture and readiness, cloud AI platforms, enterprise integration patterns, AI governance, security ...

Claude Code, Codex, Kiro), governance, and cybersecurity. You will bridge the gap between frontier AI capabilities (large language models, multimodal foundation models, retrieval-augmented generation, speech-to-speech models) and real-world energy environments, from operational productivity to developer platforms and real-time trading ...

Azure (azure Open AI service, Cosmos DB)PythonLangGraphNeo4j/cypherOther coding languages/frameworks e.g. Java/.NetAI RAG (retrieval augmented generation)Graph RAGFew shot detectionEmbedding models/LLMs - how they work, how they are trainedWho we are:We’re a business with ...

reviews, challenge design decisions, and assess technical riskDeep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworksHands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses … delivery outcomes across the portfolioDrive architectural decisions, organizational alignment, and integration of AI-powered solutions using large language models, retrieval augmented generation, orchestration frameworks, and agentic workflowsEstablish engineering excellence through architecture reviews, code reviews, automated testing, observability, security standards, operational excellence, and machine learning ...

challenge design decisions, and assess technical risk Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses … delivery outcomes across the portfolio Drive architectural decisions, organizational alignment, and integration of AI-powered solutions using large language models, retrieval augmented generation, orchestration frameworks, and agentic workflows Establish engineering excellence through architecture reviews, code reviews, automated testing, observability, security standards, operational excellence ...

Neo4j/Knowledge Graph experience Experience with Vector Databases, Search or Indexing Strong understanding of data modelling and governance Experience supporting AI, LLM or RAG use cases Nice to have: Enterprise Knowledge Management/Knowledge Base experience Semantic Search Large-scale Search platforms AI/LLM and RAG experience Financial ...

chosen and the result measured against clear success criteria.Leading the design of generative and agentic AI solutions, including prompting, retrieval augmented generation, tool use and multi-step agent workflows, and the techniques needed to make them accurate and reliable.Selecting the right approach for each … governance forums.What you need to haveStrong, hands-on expertise with large language models and generative AI, including prompt engineering, retrieval augmented generation, fine tuning, and the design and evaluation of agentic systems that use tools and operate over multiple steps.Strong programming ability in Python ...

Engineer who can own hard technical problems end to end — from research and prototyping through to production deployment — working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers. What you'll doOwn large areas of the platform … from design through to production deployment.Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data.Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking.Build and maintain integrations between retrieval and ML components and diverse enterprise data sources ...

agentic technologies. Key responsibilities Own the technical POC from scope through to demonstration Build front-end and back-end components Design and implement RAG and retrieval capabilities Work with vector databases and/or knowledge graphs Develop agentic workflows and supporting harnesses Build evaluation frameworks and assess … iterate and demonstrate solutions Work closely with architects, data specialists and client technical teams Experience required Strong hands-on AI/LLM engineering experience RAG and retrieval architectures Agentic AI/workflows Strong software engineering capability across front and back end Azure and Azure OpenAI/OpenAI Experience ...

Software Engineer to play a leading role, bringing deep skills in cutting‐edge AI to help us invent and deliver the next generation of intelligent capabilities. Key Responsibilities Lead cutting‐edge research and development of state‐of‐the‐art AI models for Design and Manufacturing challenges within … paced, cross‐functional team Preferred Qualifications Experience with model fine‐tuning, RLHF, or building agentic tool‐use systems Familiarity with retrieval‐augmented generation, knowledge graphs, or structured enterprise data Experience deploying AI in Design, Manufacturing, PLM, or industrial domains History of patents, publications ...

workflows in Copilot Studio Build scalable components: prompt orchestration, retrieval layers, Power Automate flows, model interfaces, validation pipelines Develop and optimise RAG components - embeddings, vector queries, metadata strategies for accuracy and reliability Integrate AI agents with enterprise systems via Microsoft Graph, APIs, and Power Platform connectors Implement secure … support the satellite model across business functions Requirements Hands-on experience building solutions with LLMs, AIAPIs, Copilot Studio, or agent frameworks Strong understanding of RAG architectures, vector databases, embeddings, and retrieval optimisation Experience with Microsoft Azure AI services, cloud-native engineering, and secure deployment patterns Experience with agent ...

testing and production readiness. Test APIs and integrations across internal and external services. Validate AI-generated outputs for accuracy, relevance, consistency and grounding. Assess RAG and retrieval performance, ensuring relevant information is retrieved and used appropriately. Establish repeatable evaluation approaches and datasets for AI-enabled functionality. Work with … tooling such as Jira or Azure DevOps. Good technical understanding of web applications, APIs and modern application architectures. Experience testing Generative AI, LLM or RAG solutions would be highly desirable. Understanding of AI evaluation concepts including groundedness, relevance, hallucination testing and retrieval quality. Strong analytical, problem-solving ...