176 to 200 of 235 Retrieval-Augmented Generation Jobs in the UK

data team and creating a culture that enables growth, development and psychological safety Exploring and applying Large Language Models (LLMs) and other modern AI techniques (e.g., embeddings, retrieval-augmented generation, summarisation) to enhance internal tools, automate workflows, or develop client-facing features Acquiring, cleaning, and integrating data from internal and external sources to enrich More ❯

and wants to shape how AI is used in the physical world. 🧠 You’ll need: 2+ years' engineering experience with a builder’s mindset Hands-on with LLMs — LangChain, RAG, agents, fine-tuning, etc. Infra knowledge (cloud, containers, relational/graph DBs) Bonus: startup/founder experience 🔧 You’ll be doing: Shipping to prod from Day 1 Building end-to More ❯

and wants to shape how AI is used in the physical world. 🧠 You’ll need: 2+ years' engineering experience with a builder’s mindset Hands-on with LLMs — LangChain, RAG, agents, fine-tuning, etc. Infra knowledge (cloud, containers, relational/graph DBs) Bonus: startup/founder experience 🔧 You’ll be doing: Shipping to prod from Day 1 Building end-to More ❯

postmortems, and drive execution discipline Drive AI transformation by integrating LLMs (Codex, ChatGPT, Claude, Cursor, OpenRouter) across the SDLC Partner with platform teams to scale internal AI infrastructure (OpenWebUI, RAG, LLM gateways) Collaborate with SaaS leadership and Salesforce vendors to automate pricing, CPQ, billing, contracts, payments, and provisioning Define and maintain pricing models, subscription plans, usage-based billing, and discounting More ❯

models in production to track performance, drift, and data quality, ensuring system reliability and uptime. Collaborate with Data Scientists to containerize and productionize models and algorithms, including those involving RAG and Graph RAG approaches. Manage and optimize our cloud infrastructure for ML workloads on platforms like Amazon Bedrock or similar, focusing on performance, cost-effectiveness, and scalability. Automate the provisioning More ❯

edge product Your background looks something like: Engineering experience at tech and product-driven companies Shipping LLM-based solutions to production Experience with inference and evaluation platforms Experience with RAG, semantic search, vector stores, embedding Building features end-to-end with TypeScript, React.js, and Node.js As a person, you Are first and foremost abuilder. Are excited towork in-personfrom our More ❯

into 17 European markets over the next two years. Senior Data Scientist We are looking for an experienced and creative Senior Data Scientist to help shape the next generation of AI-driven products at Ophelos. You will lead the development of innovative, data-driven solutions that help improve the lives of people in financial difficulty at scale.The data … experimentation and A/B testing to optimise model performance and product outcomes Research, prototype, and productionise state-of-the-art LLM techniques - including fine-tuning, prompt engineering, and RAG - to build explainable, reliable AI products Collaborate closely with engineering, product, and operations teams to translate business problems into scalable data and AI solutions Work with a modern data stack …/TensorFlow, visualisation libraries) 4+ years of experience delivering machine learning products end-to-end in production Hands-on experience with LLMs - fine-tuning, prompt engineering, vector databases, or RAG pipelines Proven experience with A/B testing, experimentation design, or causal inference to guide product decisions Exposure to Databricks, MLflow, AWS, and PySpark (or similar technologies) is a plus More ❯

Working at the forefront of Generative AI, this role is ideal for Applied AI Engineers who thrive in fast-paced environments and want to help shape the next generation of AI applications for well-known brands. From sports broadcasters to Tier 1 banks. What You'll Need: Proven ability to develop and deploy end-to-end, scalable … AI solutions using Python programming Solid understanding of microservices architecture, CI/CD (Github Actions) and data pipelines powering AI-driven applications Deep knowledge of LLMs, fine-tuning, prompting, RAG and Agentic frameworks. Especially integration with the OpenAI API GPT, Gemini, LLama, Claude etc. Experience designing and implementing robust quality assurance/testing frameworks for AI performance Ability to collaborate … you know your way around all the following: Langchain, Lang graph, Agentic Frameworks, LLarma Python, JavaScript, TypeScript, AWS/GCP/Azure, Spark/Data Bricks, FastAPI/Flask, RAG, LLMs, GenAI, AI Solutions, Data Pipelines, Microservices, Solution Design, Software Development, Restful APIs, Chatbots, CI/CD Github Actions, AI Engineering, Unit Testing, Vector Databases Please note: This role does More ❯

with product leaders, data engineers, software engineers, AI engineering specialists, and the Director of Data and AI, you will help develop cutting-edge solutions for Nourish's next-generation products. Role and Responsibilities: Support the design, development, and deployment of scalable AI-driven solutions. Collaborate closely with teams to understand product requirements and assist in translating them into … Help implement GenAI architectures using best-in-class frameworks and tools. Contribute to developing solutions leveraging Azure technologies, specifically Azure OpenAI API. Participate in the development and optimization of RAG architectures, embedding strategies, indexing, and chunking methods. Assist in managing evaluation frameworks and pipelines, including using tools such as llangfuse. Contribute to the documentation and sharing of best practices around … AI stack Good understanding and hands-on experience with GenAI tools and open-source and commercial large language models (LLMs). Familiarity with AI architectures such as Agentic AI, RAG (including GraphRAG) Experience with frameworks and tools such as LangChain, LlamaIndex, and evaluation pipelines (e.g., llangfuse). Strong collaborative and communication skills. A proactive learner with a strong desire to More ❯

and build powerful APIs that bring next-gen intelligence to our platform. Working across research, product, and engineering, you'll deliver real-world solutions using technologies like Retrieval-Augmented Generation and cloud-based AI tooling from Microsoft, AWS, and Google. You'll be part of a dynamic team pushing the boundaries of what's … the sports betting industry through AI, providing a vibrant and collaborative working environment. The opportunity to build on our established machine learning capabilities and help shape the next generation of AI-powered betting experiences. Access to cutting-edge tools , resources, and training to support your growth and development in the rapidly evolving AI landscape. The chance to see More ❯

Hiring: Senior AI Engineer (LLMs, Agents, RAG) Location: Remote (UK or Canada) Type: Full-time | Permanent Salary: Up to £130,000 or $240,000 Canadian Are you passionate about building real AI systems that get used in production? Interested in LLMs, RAG pipelines, and agentic software, with the freedom to make a real impact? My client are a well-funded … and fast iteration. No fluff, just outcomes. They're now looking for engineers who want to help shape that future. What You'll Be Working On: Building and optimising RAG pipelines including chunking, embeddings, and vector search Creating full LLM integrations using OpenAI, Hugging Face, and orchestration frameworks Developing robust AI agent systems with tool chaining and multi-step logic … scales in production environments What They're Looking For: 3+ years' experience as a full-stack engineer with strong Python skills Proven track record with LLMs, agentic systems, and RAG pipelines Experience with vector databases, embeddings, and semantic search Solid grasp of prompt engineering and LLM integration best practices Familiarity with containerisation, API design, and modern ML deployment tools Bonus More ❯

We are looking for brilliant engineers to join our team at Magentic. We're pushing the boundaries of AI with next-generation agentic systems that can manage entire workflows. We're focusing on a three trillion dollar market of supply chains and procurement. Our mission is to make global manufacturing supply chains robust to an ever-changing world … and event buses (Kafka, Pulsar). Wrangle large, heterogeneous data sets -model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced workloads Develop enterprise-level next generation AI systems with the support of Magentic's AI specialists Ship complete customer features -from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user … contract. Thrive in an early-stage, high-ownership environment-prototype today, deploy tomorrow, iterate next week. Bonus Points Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. Familiarity with supply-chain, procurement, or manufacturing domains. Benefits Compensation and Benefits At Magentic More ❯

complex customer projects involving co-training, fine-tuning, and various special projects. • Evaluate and improve the performance of our models on a variety of use cases (e.g., reasoning, code, RAG, tool use, agents) and across modalities (text, image, speech). • Develop complex use cases with our customers, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production … data science. • You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products • You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases • You have deep understanding of concepts and algorithms underlying machine learning and LLMs • You're experienced with building and deploying LLMs or NLP applications • You have More ❯

London, the postdoc will work on shaping the future of AI-driven shopping experiences at Amazon. In particular, the project focuses on conversational search in shopping, developing next-generation conversational search systems in the shopping domain that seamlessly bridge natural shopping dialogues with precise product retrieval and recommendation. Key challenges include developing new methods for grounding … techniques in a variety of areas and innovate on behalf of shoppers, advertisers, and customers. In this role you will: Lead research projects in conversational search and retrieval-augmented systems Develop novel architectures combining dialogue management with product search Design and implement evaluation frameworks for agentic conversational shopping systems Publish research findings in top-tier conferences … Machine Learning, Information Retrieval or related field Strong publication record in NLP, Information Retrieval, or Conversational AI Experience with large language models and retrieval-augmented generation Research background in conversational systems or dialogue management Experience with modern deep learning frameworks (PyTorch, TensorFlow) Excellent written and verbal communication skills PREFERRED QUALIFICATIONS More ❯

ll take the lead in shaping end-to-end Azure AI architectures, from discovery and PoCs through to delivery and optimisation. You'll work directly with enterprise clients, defining RAG systems, Agentic AI solutions, knowledge base integrations, and driving forward both client success and internal AI accelerators. Key Responsibilities: Design scalable, secure Azure AI architectures tailored to client needs. Work … closely with customer business and technical stakeholders. Define and deliver solutions involving RAG systems, Agentic AI, knowledge bases, and MCP integrations. Lead pre-sales engagements including PoCs, workshops, and stakeholder briefings. Collaborate with engineers, analysts, and scientists to guide delivery. Ensure best practice in responsible AI, data management, and security. Monitor performance and optimise ongoing AI solutions. Contribute to internal More ❯

AI architectures from the ground up Gathering business and technical requirements and translating them into robust AI solutions Selecting, training, and integrating AI/ML models , including LLMs and RAG pipelines Deploying AI solutions across AWS, Google Cloud, and Microsoft Azure Building end-to-end solutions from prototype to production, ensuring scalability and performance Collaborating with C-suite stakeholders, engineers … AI Hands-on experience building AI solutions from concept to delivery Strong experience with cloud platforms : AWS, Google Cloud Platform (GCP), and Microsoft Azure Expertise in model selection, LLMs, RAG, and ML Ops pipelines Strong stakeholder engagement skills with experience leading business-critical AI initiatives Why apply? Opportunity to lead end-to-end Generative AI integration for high-profile programmes More ❯

viewing in real time using image embeddings, similarity search (e.g. CLIP, vector search), and traditional CV approaches (e.g. YOLO, MobileNet). Design and implement pipelines that support retrieval-augmented generation, internal AI tools, and scalable content delivery. Experience with vector databases, agent frameworks, or data workflows is highly relevant. Own model deployment pipelines, including More ❯

support secure, air-gapped AI deployments, with a focus on NLP-based tooling * Develop pipelines for transcription ingestion and real-time analytical insight generation * Support graph and RAG-based inference layers using data from structured and unstructured sources * Build and expose APIs for frontend consumption, enabling natural-language querying, dynamic visualisation, and reporting * Ensure system portability via containerisation More ❯

serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to More ❯

production (e.g., MLOps, CI/CD for ML, model versioning) Build systems that integrate AI into key parts of our stack, such as: Forecasting customer demand and renewable generation Dynamic pricing and energy trading algorithms Intelligent alerts and personalized customer features Work closely with product and engineering leadership to identify high-impact AI opportunities Build and lead a … product teams Clear communication and an ability to prioritize for both experimentation and reliability Bonus Familiarity with optimization, time series modeling, or forecasting Experience with large language models (LLMs), RAG, or generative AI in production Background in MLOps or AI infrastructure at scale Competitive salary and a stock options sign-on bonus Biannual bonus scheme Fully expensed tech to match More ❯

production (e.g., MLOps, CI/CD for ML, model versioning) Build systems that integrate AI into key parts of our stack, such as: Forecasting customer demand and renewable generation Dynamic pricing and energy trading algorithms Intelligent alerts and personalized customer features Work closely with product and engineering leadership to identify high-impact AI opportunities Build and lead a … product teams Clear communication and an ability to prioritize for both experimentation and reliability Bonus Familiarity with optimization, time series modeling, or forecasting Experience with large language models (LLMs), RAG, or generative AI in production Background in MLOps or AI infrastructure at scale Competitive salary and a stock options sign-on bonus Biannual bonus scheme Fully expensed tech to match More ❯

and help lay the foundations for their Agentic AI Journey. What you'll do: Architect and deploy robust, multi-agent systems using Google's ADK Design and implement advanced RAG pipelines to provide agents with deep contextual understanding Design, build, and maintain a suite of secure and scalable Model Context Protocol MCP servers Own the full lifecycle of agent development … from initial design and prototyping to deployment, monitoring, and continuous improvement Experience required: Proven background in similar AI/ML Roles Strong proficiency in Python & SQL Demonstrable experience with RAG, Agentic AI, Googles ADK (Or similar LLM Application frameworks), API Design & Consumption Role details: AI Engineer Hybrid - 3 days p/w in Central London £60,000 - 75,000/ More ❯

not, and what to test next. Translate raw data into board-level insights - clear, concise, commercially relevant, and rooted in rigorous analysis. Leverage AI/ML tools (e.g. LLMs, RAG, clustering, regression) to build smarter internal tools and identify untapped growth levers. Design, implement, and interpret A/B tests and experiments that directly inform roadmap prioritisation and go-to … automation. Comfortable using BI tools such as Tableau, PowerBI, Looker, or Lightdash, and running analysis in statistical packages. Familiarity with LLMs and AI-powered tools to support insight generation, automation, and experimentation. Proven track record of influencing senior stakeholders with data storytelling and commercial acumen Deep understanding of marketplace KPIs: CAC, LTV, take-rate, sale rate, funnel conversion More ❯

growth and investment, specifically within our high-priority systematic trading and analytics systems. We are seeking a hands-on Engineering Lead to drive the development of our next-generation quantitative development platform serving the Equities Cash, Derivatives, and Prime businesses. This is a unique opportunity to make a significant impact as the platform enters its key growth phase. … Docker, Kubernetes) Proven success in enhancing developer experience that reduces friction in coding, building and deploying APIs and client libraries. Real-world application of generative AI prompt engineering and RAG pipelines. Full-stack HTML5 web development skills. Desired Skills: Understanding of Equities Cash, D1 & Deriv market mechanics and products via sell-side trading projects Familiarity with low-latency programming languages More ❯

support secure, air-gapped AI deployments, with a focus on NLP-based tooling * Develop pipelines for transcription ingestion and real-time analytical insight generation * Support graph and RAG-based inference layers using data from structured and unstructured sources * Build and expose APIs for frontend consumption, enabling natural-language querying, dynamic visualisation, and reporting * Ensure system portability via containerisation … clear grasp of the constraints and workarounds involved * Comfort designing APIs for real-time and batch AI/ML pipelines. * Experience supporting or building graph-based systems (e.g., for RAG or knowledge graph traversal) is a plus Experience working with LLMs, vector stores, or transcription pipelines Experience in Defence, aerospace, or other secure environments Due to the nature and urgency More ❯