76 to 100 of 111 Retrieval-Augmented Generation Jobs in England

AI - backed by a strong mathematics and statistics foundation. This includes hands-on experience with large language models (LLMs), foundation models, and autonomous agent frameworks, alongside expertise in implementing RAG systems, designing prompt engineering frameworks, and developing multi-agent systems. You should be proficient with both commercial and open-source technologies, including popular frameworks like LangChain, Hugging Face, and PyTorch … the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures. Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and MLOps best practices. Share insights through AWS Blogs, public speaking events, and technical communities. - Build and nurture an internal AWS community of AI/ML experts … deep expertise in traditional machine learning and deep learning. Must have experience building production-grade AI systems, complemented by practical knowledge of modern Generative AI technologies (LLMs, foundation models, RAG systems) and autonomous agent frameworks. Strong background in AI architecture patterns and MLOps practices, with demonstrated ability to design and deploy enterprise-grade AI solutions at scale. PREFERRED QUALIFICATIONS - Experience More ❯

paced environment. Hands-on with Next.js, Typescript (React/Node), Tailwind, SQL (Prisma), and Azure . Bonus points for experience with: LLM APIs (OpenAI, Anthropic), Retrieval Augmented Generation pipelines, Python, serverless architecture, or Microsoft Office Add-ins. Strong product mindset and passion for building. You may have tried a startup yourself or hacked together More ❯

use cases Site search solutions (e.g. Yext, Algolia, Elasticearch) Headless CMS/DXP platforms (Contentful, Sitecore, AEM etc) REST/GraphQL APIs Modern Web Development & Accessibility Analytics platforms LLMs, RAG, and Graph Database concepts You must be a natural storyteller who simplifies complexity, engages executives, and builds trust quickly. You have an ability to develop business cases that communicate requirements More ❯

AI pipelines. What You'll Bring Deep solution architecture experience across cloud, data, and business platforms. Proven experience designing or integrating AI/GenAI solutions such as copilots, chatbots, RAG systems, or automation tools. Understanding of GenAI and agentic design patterns, including orchestration frameworks and RAG. Experience with event-driven systems, messaging platforms, and APIs. Familiarity with AI governance standards More ❯

goals into clear technical execution through strong communication and cross-team alignment. Nice to Have Experience with orchestration frameworks ( LangChain, LangGraph ) and multi-agent workflows Knowledge of vector databases, RAG pipelines, and lightweight model hosting Ability to design data pipelines and feedback loops for improving AI-driven features Awareness of emerging AI areas such as multimodal, edge AI, or AI More ❯

agents that drive measurable customer value. Key Responsibilities: Designing and improving agentic systems that break down complex tasks into actionable steps. Developing innovative context engineering strategies (e.g., retrieval-augmented generation, dynamic context construction, memory optimisation). Select, benchmark, and host LLMs on Amazon SageMaker or EKS , comparing and optimising models to ensure agentic systems More ❯

employee queries, policy navigation). Design and deploy conversational agents using LangChain and AutoGen for internal use. Build modular and scalable pipelines using LangGraph for multi-agent orchestration. Integrate RAG systems to enable context-aware document retrieval from internal HR/legal databases. Required Skills & Experience: Solid exposure in AI/ML engineering, with a strong focus on … NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability to translate technical concepts for non-technical More ❯

employee queries, policy navigation). Design and deploy conversational agents using LangChain and AutoGen for internal use. Build modular and scalable pipelines using LangGraph for multi-agent orchestration. Integrate RAG systems to enable context-aware document retrieval from internal HR/legal databases. Required Skills & Experience: Solid exposure in AI/ML engineering, with a strong focus on … NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability to translate technical concepts for non-technical More ❯

them for production, and putting the right evaluation and governance around them. What you'll do Build GenAI tools end-to-end (independently): chat/assistants, document Q&A (RAG), summarisation, classification, extraction, and workflow/agent automations. Own evaluation & safety : create offline/online eval sets, measure faithfulness/hallucination, bias, safety, latency and cost; add guardrails and red … ability to ship independently : from idea prototype secure, supportable production tool. Strong Python & SQL ; solid software engineering habits (testing, versioning, CI/CD). Practical LLM skills: prompt design, RAG , tool/function calling, evaluation & guardrails , and prompt/model observability. Sound grasp of statistics/experimentation (A/B tests, hypothesis testing) and communicating impact to non-technical audiences. More ❯

for AI engineering across the enterprise, ensuring alignment with organizational priorities and technology roadmaps. Architect for Scale : Drive architectural decisions for platforms and applications that leverage LLMs, retrieval-augmented generation, AI agents, and unstructured data processing at enterprise scale. Influence & Align : Partner with senior engineering leaders, product managers, business stakeholders, and governance teams to … Expertise in modern software architecture, distributed systems, and cloud infrastructure (AWS, Azure, or GCP). Deep hands-on experience integrating AI/ML systems into production environments, including LLMs, RAG, vector search, and AI agents. Strong ability to communicate technical strategy to executives, engineers, and business partners alike. Proven ability to set and enforce engineering standards for quality, security, and More ❯

Senior Gen AI Engineer – London (Hybrid) - £90-120k Prompt Engineering | RAG Pipelines/Vector DB | OpenAI & LangChain | Flexible Working Ada Meher is currently working with an equity backed SaaS software vendor in the construction space who are recruiting a Senior AI Engineer with skills in LLM, RAG pipeline builds & fine-tuning and optimisation of prompts & models to join their … Node/Typescript or similar Experience with relevant technologies such as OpenAI, LangChain/LangGraph, LlamaIndex Experience with Hugging Face and LoRA/QLoRA for fine-tuning Experience with RAG & Vector DBs eg. FAISS, Weaviate, Pinecone Any experience of MLOps with MLFlow, AWS (SageMaker), CI/CD (GitHub Actions) or similar would be a benefit to an application The employer More ❯

its business milestones. Responsibilities (including but not limited to): Backend APIs (Python/FastAPI): Build reliable, secure services that power AI features and data retrieval at scale. RAG & vector search: Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration … hardworking and dedicated, with an entrepreneurial/ownership mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems , vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings , and hybrid search (BM25 + vectors). Strong grasp of chunking strategies , metadata, indexing, recall/precision More ❯

its business milestones. Responsibilities (including but not limited to): Backend APIs (Python/FastAPI): Build reliable, secure services that power AI features and data retrieval at scale. RAG & vector search: Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration … hardworking and dedicated, with an entrepreneurial/ownership mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with RAG systems, vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings, and hybrid search (BM25 + vectors). Strong grasp of chunking strategies, metadata, indexing, recall/precision More ❯

strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world … roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate … in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD More ❯

strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world … roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate … in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD More ❯

learning and innovation Requirements: Experience with at least one programming language such as Python, TypeScript, React, or C sharp Familiarity with large language models, APIs, prompt engineering, retrieval-augmented generation, or vector databases Understanding of software deployment pipelines and continuous integration and continuous delivery tools Ability to troubleshoot and resolve AI-related issues. Experience More ❯

Full Stack AI Software Engineer - Full Remote UK - £90,000 + Equity This role requires a software engineer with experience in implementing RAG pipelines and Vector Search (and hybrid AI searches, preferably). The client I am working with is an AI focused start-up backed by a £1.7M pre-seed investment. They are on a mission to streamline the … an early stage. What you'll work on: Backend APIs (Python/FastAPI): Build and maintain secure, high-performance services that drive AI features and data access at scale. RAG & vector search: Design and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate … AI development. Requirements: A motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient More ❯

BE DOING Build intelligent workflows using n8n, Microsoft Power Automate, Flowable, and similar tools. Design and implement agentic AI solutions, integrating LLMs and frameworks such as LangChain, AutoGen, and RAG pipelines with platforms like OpenAI. Collaborate with teams across the business to identify automation opportunities and enhance efficiency. Contribute to the company's AI and workflow automation architecture, ensuring scalability … Engineer - Essential Skills Hands-on experience with workflow automation tools such as n8n, Microsoft Power Automate, or Flowable. Strong understanding of LLM integration and agentic AI frameworks (LangChain, AutoGen, RAG). Proficiency in Python or JavaScript for scripting and workflow logic. Familiarity with APIs, event-driven architectures, and cloud platforms (Azure, AWS, or GCP). TO BE CONSIDERED... Please either More ❯

Senior Analytics Developer Are you ready to elevate your analytics career to new heights? Would you thrive in a dynamic environment, developing solutions that drive insights and innovation? About Team: The role will report to the Analytics Manager. You will More ❯

distributed systems, and enterprise architecture Experience with Claude Code for agentic coding and AI-powered development Proven track record in financial services or regulatory compliance environments Expert knowledge of RAG architectures, advanced RAG patterns, and vector database optimization Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP) Proven ability to architect and scale … frameworks using LangGraph, LangMem, and custom agent orchestration Lead technical strategy for Azure OpenAI GPT-5 integration and advanced embedding-based retrieval systems Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) Architect Small Language More ❯

distributed systems, and enterprise architecture Experience with Claude Code for agentic coding and AI-powered development Proven track record in financial services or regulatory compliance environments Expert knowledge of RAG architectures, advanced RAG patterns, and vector database optimization Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP) Proven ability to architect and scale … frameworks using LangGraph, LangMem, and custom agent orchestration Lead technical strategy for Azure OpenAI GPT-5 integration and advanced embedding-based retrieval systems Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) Architect Small Language More ❯

distributed systems, and enterprise architecture Experience with Claude Code for agentic coding and AI-powered development Proven track record in financial services or regulatory compliance environments Expert knowledge of RAG architectures, advanced RAG patterns, and vector database optimization Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP) Proven ability to architect and scale … frameworks using LangGraph, LangMem, and custom agent orchestration Lead technical strategy for Azure OpenAI GPT-5 integration and advanced embedding-based retrieval systems Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) Architect Small Language More ❯

distributed systems, and enterprise architecture Experience with Claude Code for agentic coding and AI-powered development Proven track record in financial services or regulatory compliance environments Expert knowledge of RAG architectures, advanced RAG patterns, and vector database optimization Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP) Proven ability to architect and scale … frameworks using LangGraph, LangMem, and custom agent orchestration Lead technical strategy for Azure OpenAI GPT-5 integration and advanced embedding-based retrieval systems Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) Architect Small Language More ❯

Team, you'll design and build next-generation automation platforms, blending Python, React, Postgres, and modern DevOps practices with cutting-edge AI/ML techniques such as RAG, vector databases, and multi-agent systems. You'll work across the full software lifecycle: from system design and test automation, to deployment and performance monitoring, collaborating with some of the … in the industry. What You'll Work On Designing and developing automation solutions aligned with Apple's product requirements. Building agentic AI/ML systems (MCP servers/clients, RAG pipelines, vector DBs). Developing both front-end (React, JS) and back-end (Python, APIs, Postgres) features. Driving test automation with Selenium and iOS functional frameworks. Implementing CI/CD … experience with Selenium and iOS functional automation. Strong React/JavaScript UI development background. Back-end engineering with Python + Postgres. AI/ML expertise in LLMs, embeddings, and RAG systems. Experience with ETL pipelines, vector databases, and modern DevOps (Jenkins). Bonus points for: Multi-agent system design. Graph database experience. Familiarity with Charles Proxy, Git, Jenkins. Role Details More ❯

independent travel entrepreneurs worldwide, weve always believed in the power of personal service. Now, were using AI to scale care, creativity, and connection like never before. Our next-generation travel platform is being transformed by intelligent features, with TC Co-Pilot at the heart of it. As AI Product Owner, youll lead the charge in embedding smart systems … e-commerce, or hospitality Conversational interfaces, semantic search, or recommendation engines Ethical AI frameworks, GDPR, and trust-by-design principles Building AI features using tools like LangChain, Pinecone, or RAG architectures More ❯