401 to 425 of 498 Retrieval-Augmented Generation Jobs in London

Curve Maintain a current and deep understanding of the evolving Generative AI and Agentic AI landscape - frontier models, AI patterns, prompt engineering, fine-tuning, RAG architectures, and multi-agent orchestration. Translate complex technical concepts into clear business value propositions specific to Fund Services operations and clients. Fund Services is building … cloud architectures, distributed systems, and modern software development practices Deep understanding of the Generative AI ecosystem - frontier models, AI patterns, prompt engineering, fine-tuning, RAG, and agentic architectures Proven ability to move from problem identification to working prototype at pace - with a portfolio of real things built, not just planned ...

pipelines, entity extraction, classification, ranking, search, recommendation, data quality, knowledge graph enrichment, predictive analytics, LLM-based systems, Gen AI Agents, Multi Agent systems and RAG where relevant. You will work closely with product, engineering, content, domain experts, and business stakeholders to deliver scalable, measurable, and production-ready data science solutions … chemical entities, drugs, genes, diseases, clinical trials, safety data, publications, patents, metadata, and ontologies. Guide the use of modern AI approaches, including embeddings, LLMs, RAG, prompt-based workflows, and GenAI evaluation, where they add clear customer and business value. Partner with engineering to ensure solutions are robust, scalable, maintainable ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

team and use case. Enablement & Integration Deploy vector database and retrieval infrastructure (e.g., Databricks AI Search) to support Document AI and RAG use cases. Align platform controls with Databricks and Unity Catalog governance patterns. Provide clear documentation, reusable patterns, and self-service onboarding guidance so delivery squads … from the crowd Experience with AI gateways, LLM proxies, or model-routing patterns. Exposure to AI observability tools, vector databases (Databricks AI Search), RAG pipelines, or non-deterministic system monitoring. Hands-on experience implementing policy-as-code, action logging, or AI kill switches. Direct experience with Okta, ZScaler, Entra ...

Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. … understanding of highly scalable and reliable distributed systems hosted on public cloud platforms. Experience building document retrieval and understanding systems, such as RAG, to accurately ingest large-scale client knowledge into client agents and applications. A strong track record of independently owning and delivering successful engineering projects, including ...

release increment, including data flows, integration sequencing, and non-functional requirements (performance, scalability, security) baked in at design time Own the technical implementation pattern (RAG pipeline design, prompt/agent orchestration, model integration via APIs) and work directly with data science/ML engineering teams during build. Sit in sprint … program/product roadmap into solution designs and detailed architecture specs for Commercial Digital Solutions Define architecture patterns for GenAI/LLM-based solutions (RAG, agentic workflows, model orchestration), evaluate build-vs-buy for AI capabilities Architect integration patterns between Commercial systems and the enterprise data platform/data lake ...

for. What you'll be working on as an AI Engineer - LLM & Agentic Systems: Designing and building AI agents and agentic workflows - combining LLMs, RAG, reasoning, memory and tool orchestration to solve real, complex business problems. Owning delivery end-to-end - from initial exploration through to production deployment, integration … with clear, real-world examples you can speak to confidently. Hands-on experience building AI agents including tool use, orchestration and multi-step reasoning - RAG systems that actually deliver, not just proofs of concept. Strong Python skills and solid machine learning foundations - able to write clean, production-grade code with ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

looking for an experienced Agentic AI Engineer to join a pioneering team building next-generation AI solutions. You'll work on cutting-edge projects involving LLMs, Neo4j, Knowledge Graphs, GraphRAG, and AI Agents , helping unlock greater context, reasoning, and automation from their data. Key Responsibilities: Design and develop … teams to deliver production-ready AI systems Required Skills: Strong Python development experience Hands-on experience with Neo4j and Knowledge Graphs Experience with LLMs, RAG, or GraphRAG architectures Understanding of AI agents and autonomous workflows Cloud experience (AWS, Azure, or GCP) Desirable: LangGraph, LangChain, CrewAI, AutoGen, or similar frameworks Experience ...

Engineer to design, build, and deploy production-ready Generative AI systems. Role You will own the full lifecycle of GenAI applications, working with LLMs, RAG architectures, and agentic frameworks to deliver scalable, business-focused solutions. Responsibilities Build and deploy GenAI and RAG systems Develop agentic AI workflows Design prompts … clients and technical teams Requirements 1-3 years deploying LLM/GenAI systems in production Strong Python skills Experience with cloud platforms Knowledge of RAG, vector databases, and LLM frameworks Git and CI/CD experience Experience with LangChain and LangGraph AWS experience IT/Technology-related university degree (minimum ...

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 ...

just getting started. Recognised by EGR as one of the most innovative startups in gaming, we\'re scaling fast and shaping the next generation of sports entertainment. We\'ve built a product that users genuinely love — with unlimited betting group chats, multi-game bet builders, and an experience … explain what broke and what you changed. Hands-on with an agent framework (LangGraph, LlamaIndex, Semantic Kernel, ADK or similar) and RAG in production: embedding models, vector stores, re-ranking, and knowing when a live query beats retrieval. Strong Python experience or similar, on a real engineering foundation: testing, version ...

ensuring successful business adoption. The role will suit someone who can combine strategic AI leadership with practical delivery experience across GenAI, LLMs, Agentic AI, RAG, enterprise automation, responsible AI, cloud platforms, and operating model transformation. Key Responsibilities Lead enterprise AI and GenAI delivery programmes from strategy to implementation. Define … cases across enterprise automation, predictive analytics, document intelligence, compliance monitoring, fraud detection, payments, lending, customer service, and workflow optimisation. Oversee the delivery of LLM, RAG, Agentic AI, Conversational AI, and multi-agent solutions. Lead vendor selection, programme mobilisation, stakeholder management, and delivery governance. Work with executive stakeholders to align ...

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 ...