1 to 25 of 654 Permanent Retrieval-Augmented Generation Jobs in London

improve how users discover, synthesize, and interact with scientific knowledge.Our work spans semantic search, retrieval-augmented generation (RAG), ranking systems, LLM evaluation, online experimentation, and scalable evaluation infrastructure. We partner closely with Product, Engineering, UX Research, Knowledge Graph, and Applied AI teams to deliver … + Search relevance and ranking quality. + Semantic retrieval and vector search + Retrieval-augmented generation (RAG) + AI grounding and hallucination mitigation + User discovery and engagement outcomes* Establish scalable evaluation methodologies for search, retrieval, recommendation, and LLM-powered ...

evaluation, ranking optimization, and AI system quality.Lead initiatives focused on improving:Search relevance and ranking quality.Semantic retrieval and vector searchRetrieval-augmented generation (RAG)AI grounding and hallucination mitigationUser discovery and engagement outcomesEstablish scalable evaluation methodologies for search, retrieval, recommendation, and LLM-powered … high-performing technical teams in complex, cross-functional organizations.Deep expertise in:Search relevance and ranking systems.Information retrieval and semantic searchRetrieval-augmented generation (RAG)Evaluation methodologies for IR and generative AI systemsExperimentation frameworks and A/B testingStrong experience with:Vector retrieval ...

optimization, and AI system quality. Lead initiatives focused on improving: Search relevance and ranking quality. Semantic retrieval and vector searchRetrieval-augmented generation (RAG)AI grounding and hallucination mitigationUser discovery and engagement outcomesEstablish scalable evaluation methodologies for search, retrieval, recommendation, and LLM-powered … technical teams in complex, cross-functional organizations. Deep expertise in: Search relevance and ranking systems. Information retrieval and semantic searchRetrieval-augmented generation (RAG)Evaluation methodologies for IR and generative AI systemsExperimentation frameworks and A/B testingStrong experience with: Vector retrieval ...

team. The ideal candidate will have a deep understanding of Generative and Agentic AI, LLMs, retrieval-augmented generation (RAG), machine learning, and modern interoperability standards such as the Model Context Protocol (MCP), along with a proven track record of architecting and implementing innovative, enterprise … skills that let agents perform specialized, domain-specific tasks reliably, securely, and consistently across teams.• Retrieval-Augmented Generation (RAG) & Knowledge Architecture: Expertise architecting RAG and knowledge-grounded systems—chunking strategies, embeddings, vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and retrieval ...

solutions for documentation, SDKs, configurations and pipelines to enable rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor … secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented ...

solutions for documentation, SDKs, configurations and pipelines to enable rapid deployment of GenAI applications (including Retrieval-Augmented Generation (RAG) pipelines) and agents with planning, memory, and workflow orchestration Implement tools and frameworks for model versioning, experiment tracking, and lifecycle management Develop systems to monitor … secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented ...

services.Drive adoption of AI/LLM technologies across Private Markets products, including prompt engineering, Retrieval-Augmented Generation (RAG), AI-assisted workflows, and intelligent automation where they deliver measurable business value.Lead and develop a team of engineers, fostering a strong engineering culture focused on innovation … languages.Experience with AI/ML technologies and hands-on knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, or similar Generative AI technologies is highly desirable.Familiarity with AI orchestration frameworks (e.g. LangChain, Semantic Kernel, AutoGen, or similar) would ...

services. Drive adoption of AI/LLM technologies across Private Markets products, including prompt engineering, Retrieval-Augmented Generation (RAG), AI-assisted workflows, and intelligent automation where they deliver measurable business value. Lead and develop a team of engineers, fostering a strong engineering culture focused … Experience with AI/ML technologies and hands-on knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, or similar Generative AI technologies is highly desirable. Familiarity with AI orchestration frameworks (e.g. LangChain, Semantic Kernel, AutoGen, or similar) would ...

enterprise AI platform that powers AI products across 9fin.Develop scalable AI services supporting Agentic AI, Retrieval-Augmented Generation (RAG), embeddings, vector search, model serving, and intelligent automation.Build orchestration layers that transform structured and unstructured enterprise data into reusable AI capabilities.Develop production-ready AI applications … applications powered by Large Language Models (LLMs).Have experience building Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG) solutions, making use of embeddings, vector databases, and modern LLM orchestration frameworks.Have experience building or contributing to agentic AI systems, intelligent workflows, or orchestration frameworks.Backend ...

enterprise AI platform that powers AI products across 9fin.Develop scalable AI services supporting Agentic AI, Retrieval-Augmented Generation (RAG), embeddings, vector search, model serving, and intelligent automation. Build orchestration layers that transform structured and unstructured enterprise data into reusable AI capabilities. Develop production-ready … applications powered by Large Language Models (LLMs).Have experience building Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG) solutions, making use of embeddings, vector databases, and modern LLM orchestration frameworks. Have experience building or contributing to agentic AI systems, intelligent workflows, or orchestration ...

ready AI solutions using modern Azure technologies and cloud-native architecture.Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications.Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences.Work closely with Product, Business … Services and cloud-native application development.Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases.Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms.Strong understanding of software ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

have designed enterprise-scale agentic systems end-to-end, but you must have meaningful hands-on experience with the core components: LLM-powered applications, RAG architectures, agent frameworks, and enterprise platform integration. You are intellectually curious, technically rigorous, and energised by working at the frontier of what is currently possible … client constraints.Designing and documenting agentic AI solution architectures — including multi-agent patterns, LLM-powered applications, retrieval-augmented generation (RAG) systems, and orchestration pipelines applied to commerce use cases such as personalisation, conversational commerce, intelligent search, and merchandising optimisation Architecting the integration between agentic ...

evaluation frameworks to measure quality, reliability, and business impact. Improve model performance through prompt engineering, retrieval-augmented generation (RAG), and other applied AI techniques. Ensure AI systems are accurate, trustworthy, and deliver a high-quality user experience. Design for Trust and Control Build … application development. Strong programming skills in both Python and Java. Experience building backend services and APIs. Hands-on experience with AI agents, RAG systems, prompt engineering, or related applied AI techniques. Ability to balance rapid experimentation with production-quality engineering. Excellent problem-solving and communication skills. Relevant Technologies Candidates should ...

emerging AI capabilities across security operations, leveraging machine learning, generative AI, agentic workflows, and Retrieval-Augmented Generation (RAG) to enhance analysis, automate decision-making, and accelerate security response.As the successful candidate, you will combine strong hands-on technical expertise with the ability to provide … within operational environments, including familiarity with Large Language Models (LLMs), Generative AI, AI agents, and Retrieval-Augmented Generation (RAG) concepts.Strong knowledge of system integration techniques, REST APIs, authentication mechanisms, and alert-driven architectures.Experience translating business and operational requirements into scalable technical solutions.Strong analytical ...

enabled products.Partner closely with engineering teams to build intelligent experiences leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), conversational interfaces, and agentic workflows.Collaborate with analytics, data, engineering, and business stakeholders to understand customer needs and identify opportunities to create value through AI-driven … Large Language Models (LLMs), conversational AI, or machine learning-powered experiences.Understanding of concepts such as retrieval-augmented generation (RAG), AI agents, orchestration frameworks, evaluation approaches, or similar AI product patterns.Strong analytical and problem-solving skills, with the ability to use data and customer insights ...

products. Partner closely with engineering teams to build intelligent experiences leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), conversational interfaces, and agentic workflows. Collaborate with analytics, data, engineering, and business stakeholders to understand customer needs and identify opportunities to create value through … Language Models (LLMs), conversational AI, or machine learning-powered experiences. Understanding of concepts such as retrieval-augmented generation (RAG), AI agents, orchestration frameworks, evaluation approaches, or similar AI product patterns. Strong analytical and problem-solving skills, with the ability to use data and customer ...

Technologies team. The candidate must possess deep expertise in Generative and Agentic AI, including LLMs, retrieval-augmented generation (RAG), machine learning, and interoperability standards such as the Model Context Protocol (MCP). The role involves shaping the Generative AI strategy, selecting suitable models … through modular, reusable skills and resources; defining standards for custom tools, connectors and skills ensuring reliable, secure, and consistent operation. Retrieval‐Augmented Generation (RAG) & Knowledge Architecture – expertise in RAG and knowledge‐grounded systems, including chunking, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid ...

Solutions* Design, develop and deploy enterprise-grade AI products and services.* Build agentic AI workflows, retrieval-augmented generation (RAG) solutions and intelligent automation capabilities.* Deliver scalable integrations with LLMs, MCP services, vector databases and enterprise platforms.* Develop reusable AI frameworks, accelerators and engineering standards.Engineering … Python and modern software engineering practices.* Experience with Large Language Models (LLMs) and Generative AI.* Agent frameworks and orchestration technologies.* Retrieval Augmented Generation (RAG) architectures.* API development and microservice design.* Cloud-native development (Azure preferred).* CI/CD automation and MLOps practices.* Vector ...

Build AI SolutionsDesign, develop and deploy enterprise-grade AI products and services.Build agentic AI workflows, retrieval-augmented generation (RAG) solutions and intelligent automation capabilities.Deliver scalable integrations with LLMs, MCP services, vector databases and enterprise platforms.Develop reusable AI frameworks, accelerators and engineering standards.Engineering ExcellenceLead technical … without formal management responsibility.Technical SkillsPython and modern software engineering practices.Experience with Large Language Models (LLMs) and Generative AI.Agent frameworks and orchestration technologies.Retrieval Augmented Generation (RAG) architectures.API development and microservice design.Cloud-native development (Azure preferred).CI/CD automation and MLOps practices.Vector databases and knowledge retrieval ...

SolutionsDesign, develop and deploy enterprise-grade AI products and services. Build agentic AI workflows, retrieval-augmented generation (RAG) solutions and intelligent automation capabilities. Deliver scalable integrations with LLMs, MCP services, vector databases and enterprise platforms. Develop reusable AI frameworks, accelerators and engineering standards. Engineering … Technical SkillsPython and modern software engineering practices. Experience with Large Language Models (LLMs) and Generative AI.Agent frameworks and orchestration technologies. Retrieval Augmented Generation (RAG) architectures. API development and microservice design. Cloud-native development (Azure preferred).CI/CD automation and MLOps practices. Vector databases ...

emerging AI capabilities across security operations, leveraging machine learning, generative AI, agentic workflows, and Retrieval-Augmented Generation (RAG) to enhance analysis, automate decision-making, and accelerate security response. As the successful candidate, you will combine strong hands‐on technical expertise with the ability … implementing Artificial Intelligence (AI) capabilities within operational environments, including familiarity with Large Language Models (LLMs), Generative AI, AI agents, and Retrieval‐Augmented Generation (RAG) concepts. Strong knowledge of system integration techniques, REST APIs, authentication mechanisms, and alert‐driven architectures. Experience translating business and operational ...

portions of our AI agent infrastructure , from designing and deploying multi-agent systems to integrating Retrieval-Augmented Generation (RAG) pipelines , and evaluation frameworks . You will be responsible for delivering AI-powered features into production at scale — ensuring they are performant, reliable, and secure … deliver high-impact features. Ensure scalability, performance, and security across the stack. Develop and deploy AI-powered features in production , including RAG (Retrieval-Augmented Generation) systems, multi-agent infrastructure, and evaluation frameworks (Evals) . Create data pipelines for AI model training, evaluation, and continuous ...

operate reliably in production investment environments.Continuously evaluate and integrate emerging frameworks in multi-agent coordination, retrieval-augmented generation (RAG), and prompt design.Fuse AI and Research:Partner with fundamental and quantitative investors to identify high-value opportunities for AI-enabled automation and augmentation.Translate complex investment … LangChain, AutoGen, CrewAI, Semantic Kernel, or LangGraph).10+ years’ experience with financial modeling, portfolio construction, trading, or investment management workflows.Experience with advanced retrieval-augmented generation and multi-agent systems.Certifications such as:Databricks Certified Generative AI Engineer AssociateSnowPro Specialty: Gen AIAWS Certified Machine Learning Engineer ...

will guide cross-functional teams and strategic partners to define reference architectures and delivery roadmaps for multi-agent systems—leveraging LLMs, retrieval-augmented generation, and modern agent frameworks—while instituting governance, safety, and reliability standards and tracking measurable business outcomes.Job responsibilitiesArchitect, develop, and productionize … definition, tool integration, planning, memory, and workflow orchestration using LangChain, CrewAI, AutoGen, ADK and LangGraph.Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search using vector databases such as Pinecone and Chroma, including indexing, retrieval policies, and evaluation.Build and integrate agent tools ...