51 to 75 of 75 Retrieval-Augmented Generation Jobs in the UK excluding London

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

be necessary for meetings, but these will be fully funded. As a GenAI/Python Engineer , you’ll help design, build, and scale AI-powered applications using tools like RAG, intelligent agents, and LLMs. This hands-on, client-facing role blends technical depth with consulting impact. You will: Develop and scale GenAI solutions from POCs to production. Lead development across More ❯

high 2:1, preferably in a technical subject Proficiency in Python and its ecosystem Active engagement with the AI space and proactive exploration of new AI technologies (Agents, MCP, RAG, Chain-of-Continuous-Thought, etc. More ❯

in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured multimodal information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing and machine learning, this may be the More ❯

Weve spent 30+ years empowering over 2,200 independent travel entrepreneurs across the globe. Now, with an award-winning culture and explosive digital growth, were building the next-generation AI capabilities that will revolutionise our personal travel platform, Phenix. Were not here to follow trends. Were here to set them. This is your chance to be at the … Own key backend services: Use .NET Core/C# to build scalable APIs and services that connect human intent with machine intelligence. Build RAG-powered workflows : Leverage retrieval-augmented generation, context-aware orchestration (MCP), and internal datasets to generate real-time, contextual insights. Collaborate across disciplines: Work hand-in-hand with product designers, data … and beverages Requirements Proven experience in .NET Core/C# and modern web frameworks like Angular/TypeScript Hands-on experience with LLM APIs (OpenAI, Claude, Bedrock), LangChain, or RAG-based architectures Deep familiarity with API design, microservices, and cloud-first development (AWS, Azure, or GCP) Experience building systems with MongoDB, SQL, or vector databases like Pinecone or MongoDB Atlas More ❯

spent 30+ years empowering over 2,200 independent travel entrepreneurs across the globe. Now, with an award-winning culture and explosive digital growth, we’re building the next-generation AI capabilities that will revolutionise our personal travel platform, Phenix. We’re not here to follow trends. We’re here to set them. This is your chance to be … Own key backend services: Use .NET Core/C# to build scalable APIs and services that connect human intent with machine intelligence. Build RAG-powered workflows : Leverage retrieval-augmented generation, context-aware orchestration (MCP), and internal datasets to generate real-time, contextual insights. Collaborate across disciplines: Work hand-in-hand with product designers, data … and beverages Requirements Proven experience in .NET Core/C# and modern web frameworks like Angular/TypeScript Hands-on experience with LLM APIs (OpenAI, Claude, Bedrock), LangChain, or RAG-based architectures Deep familiarity with API design, microservices, and cloud-first development (AWS, Azure, or GCP) Experience building systems with MongoDB, SQL, or vector databases like Pinecone or MongoDB Atlas More ❯

backend engineering , ideally with Go and ML frameworks like PyTorch or TensorFlow Familiarity with MLOps , cloud infrastructure (AWS) , Kubernetes , and Terraform Experience evaluating and deploying models (including anomaly detection, RAG, and clustering) in noisy, evolving data environments Nice to Have: Experience with Perl Knowledge of threat intelligence integration and MCP architectures Location: Remote Salary: Up to £120,000 , depending on More ❯

standards are met. Implement best practices for MLOps, including CI/CD, automated testing, model versioning, and data validation. Architect integrations with vector databases, cloud platforms, and retrieval-augmented generation systems. Qualifications: 3+ years of experience delivering full-stack AI/ML applications in production. Proficiency in Python, especially with ML libraries such as More ❯

with the bank's cybersecurity and regulatory standards. Accountabilities & Responsibilities Architect and implement secure AI services from lab to production, ensuring scalability and compliance Develop robust APIs for LLMs, RAG pipelines, agentic workflows and document intelligence systems Embed cybersecurity and data privacy controls across all AI workflows (e.g., encryption, anonymisation, access logging) Collaborate with the CISO function on threat modeling … Built agentic workflows using modular LLM agents with memory, planning, and tool integration Implemented Model Context Protocol (MCP) to manage secure, auditable context injection across agentic systems Experience building RAG pipelines with strict data governance and contextual integrity Familiarity with EU AI Act, FCA cybersecurity principles, and oversight of critical systems Worked directly with cybersecurity and compliance teams in regulated … LLM Fine-tuning and prompt engineering for LLMs (e.g., GPT, Gemini, Claude) Secure deployment of LLMs via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval Implementation of grounding, context injection, and response validation mechanisms More ❯

articulate problems and construct solutions. BCS Practitioner Certificate in Enterprise and Solutions Architecture BS in Information Systems, Engineering, or related field Foundational understanding of AI concepts, including prompt engineering, RAG, and LLMs Enterprise Architecture best practices and tools (e.g., LeanIX) Experience working in a startup environment or similar Knowledge of Construction technologies and products, such as BIM, data collection apps More ❯

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 ❯

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 ❯

About the Role Base Location: Reading, Havant, Perth, Glasgow Salary: £61,620 - £72,592 and a range of other benefits to support your family, finances and wellbeing. Working Pattern: Permanent Full Time Flexible working options available The role As a More ❯

About the Role Base Location: Reading, Havant, Perth, Glasgow Salary: £61,620 - £72,592 and a range of other benefits to support your family, finances and wellbeing. Working Pattern: Permanent Full Time Flexible working options available The role As a More ❯

About the Role Base Location: Reading, Havant, Perth, Glasgow Salary: £61,620 - £72,592 and a range of other benefits to support your family, finances and wellbeing. Working Pattern: Permanent Full Time Flexible working options available The role As a 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 ❯

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 ❯

join our client in Pharma/Life Sciences. You'll be designing and building data infrastructure for an AI/ML solution and lead on prototyping and developing a RAG platform on AWS. You'll need: - Extensive AWS Data Engineering experience (S3, EC2, Glue, Lambada etc.) - NoSQL/MongoDB - Strong understanding of Data Modelling, ETL/ELT, DWH concepts - Docker …/EKS containerisation tooling - Experience building and maintaining pipelines for data workflows (CI/CD - RAG or LLM based data system experience If this sounds like you please reach out. More ❯

learning theories, and pedagogical best practices; Engineer context structures integrating with existing curricula and learning pathways; Develop dynamic frameworks adapting to diverse cultural and educational contexts Build and optimize RAG systems for intelligent content surfacing; Design multi-modal context systems integrating text, audio, visual elements; Implement real-time context adaptation based on learner progress Curate and structure educational content repositories … successful in this role, you will ideally have/be: AI/ML fundamentals including LLMs, NLP, and system architecture Programming proficiency in Python with AI/ML frameworks RAG systems and vector database experience Previous experience in educational technology, AI/ML applications, or digital learning product development (desirable) Proven experience in database design, API development, and data pipeline More ❯

part of a small, elite, cross-functional team. What You’ll Be Doing: Designing and implementing NLP pipelines for transcription, topic extraction, and summarisation Developing modular LLM workflows (e.g., RAG, graph-based reasoning) optimised for low-resource deployments Integrating structured and unstructured data: transcripts, policy documents, supply chain models Collaborating with platform engineers to containerise models for edge inference Defining … experience building and deploying NLP/LLM solutions, including summarisation, entity extraction, and topic modelling Strong Python skills with libraries such as HuggingFace Transformers, spaCy, PyTorch/TensorFlow, or RAG frameworks Experience with knowledge graphs, GNNs, or graph-enabled retrieval Proven ability to optimise ML systems for air-gapped, low-compute, or edge environments Understanding of evaluation methods More ❯

hunt for an Technical Architect who will be leading on AI Solutions - this will include: Design, Architect & deploy next-gen GenAI solutions Supercharge natural language interfaces Push boundaries with RAG models, multi-agent systems & more Build robust AI evaluation & monitoring frameworks Mentor, lead & inspire technical team in delivering AI products Experience Required Proven GenAI solution deployment (AWS Bedrock or similar … Deep knowledge of RAG models & agent workflows Experience with GenAIOps, AI security, and responsible AI Leadership skills & a builder's mindset Built and Architected an AI product, and takent to market Interview are happening WC 18/8/25 - this is a 2 stage interview process, to be undertaken remotely. All applicants must have full rights to work in More ❯

Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs Exposure to RAG architectures and vector stores (such as FAISS, Pinecone...) Prompt Engineer (AI & Data) – Could suit a Graduate/Junior or Experienced professional Location: Remote (M4/M5/M50 area preferred but flexible) Salary … the join the R&D team and design, test and refine prompts , clean and map unstructured text and structured fields into usable metadata and semantic indexes for use in RAG systems and collaborate with product and design teams to embed LLM-powered assistants into customer facing healthcare support tools. What You'll Do Work across LLM design, structured data integration … Bring Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs, documents, form data) Exposure to RAG architectures and vector stores (such as FAISS, Pinecone.....) The ability to work with and communicate with multi-disciplinary teams at all levels of an organization Any experience in a professional More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isnt a generic software build. Youll help More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isn’t a generic software build. You 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, dynam click apply for full job details More ❯