1 to 25 of 44 Remote/Hybrid Retrieval-Augmented Generation Jobs in the UK excluding London

difference in people’s lives. Your Mission We’re seeking a highly experienced, technically exceptional Lead AI Engineer to architect and deliver next-generation Generative AI and Agentic systems. You will drive end-to-end innovation, from model selection and orchestration design to scalable backend implementation, all while … Claude, Gemini as well as self-hosted LLMs along with MCP integrations Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone/ChromaDB/Weaviate/pgvector/etc), search engines such as ElasticSearch/Solr using both TF/IDF BM25 based ...

experience with: Production-level LLM applications including fine-tuning and customisation Function-calling systems or retrieval-augmented generation (RAG) architectures Full-lifecycle projects from prototyping to production Mentoring junior engineers or shaping technical direction within teams What You’ll Gain A high-impact role … with visibility and technical influence The opportunity to shape the next generation of AI platforms Hybrid working with three days per week onsite in Oxfordshire and two days remote A supportive team that values experimentation, clean engineering and continuous learning A salary ...

experience with: Production-level LLM applications including fine-tuning and customisation Function-calling systems or retrieval-augmented generation (RAG) architectures Full-lifecycle projects from prototyping to production Mentoring junior engineers or shaping technical direction within teams What You’ll Gain A high-impact role … with visibility and technical influence The opportunity to shape the next generation of AI platforms Hybrid working with three days per week onsite in Oxfordshire and two days remote A supportive team that values experimentation, clean engineering and continuous learning A salary ...

deploy Generative AI systems end to end from use-case discovery through to production Build Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, and enterprise data sources Develop agent-based workflows , orchestration layers, and multi-step reasoning systems Work extensively with open-source … experience building and deploying Generative AI or applied ML systems Strong hands-on engineering background you actively code, build, test, and deploy Experience with: RAG architectures and vector databases Hugging Face models, pipelines, and inference tooling Prompt engineering and LLM evaluation techniques Agentic systems and orchestration patterns Cloud-native experience ...

. Multi-Agent Ecosystems: Design architectures that support Agent-to-Agent (A2A) communication, orchestration, and collaboration across diverse business functions. LLM Strategy & RAG: Define model selection, fine-tuning strategies, and build Retrieval-Augmented Generation (RAG) pipelines to ensure contextual accuracy and reduced hallucinations. Context ...

intelligent, distributed systems Architecting and building AI-driven capabilities , including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) AI agents and orchestration workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using … Python or similar languages Significant experience with backend development , microservices, and distributed systems Hands-on experience with AI/ML systems , including LLMs, RAG, or vector databases Solid understanding of containerisation and orchestration (Docker/Kubernetes) Experience delivering secure, on-premise or regulated systems Proven ability to lead technically , mentor ...

intuitive user experiences. Work closely with AI researchers and ML engineers to integrate LLMs, Retrieval-Augmented Generation (RAG), and automation into production-ready applications. Ship robust, minimal-dependency code that performs efficiently in enterprise environments. Continuously iterate and refine AI-driven products, balancing user ...

intuitive user experiences. Work closely with AI researchers and ML engineers to integrate LLMs, Retrieval-Augmented Generation (RAG), and automation into production-ready applications. Ship robust, minimal-dependency code that performs efficiently in enterprise environments. Continuously iterate and refine AI-driven products, balancing user ...

party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge and working experience of AGILE methodologies. Familiarity with Databricks, and RAG application architecture a plus Experience with latency optimisation and quantisation preferred Additional Information What’s in it for you?: Competitive salary that reflects your skills, experience ...

Balancing cost, performance, and reliability Applied AI Working with Azure OpenAI APIs beyond prompt demos Retrieval-augmented generation (RAG) Embeddings, vector stores, and evaluation Guardrails, rate limiting, and failure handling Human-in-the-loop workflows Integration & automation Integrating AI into existing enterprise systems Automating ...

following skills and experience: Strong Python and SQL experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure, AWS, or GCP Benefits The successful Senior ...

using Microsoft Copilot tools to automate business workflows (e.g., HR queries, IT support, operational data retrieval). Develop custom RAG (Retrieval-Augmented Generation) solutions within Databricks to allow LLMs to reason over proprietary SMS documents and data. Integrate AI agents with enterprise … Experience with defining metrics layers (e.g., DBX semantic layer or Databricks Genie) is essential. Practical experience with Large Language Models (LLMs), Prompt Engineering, and RAG architectures. Proficient in Python (for data manipulation and API interaction) and SQL (for data modelling). Experience working with REST APIs and connecting disparate business ...

microservices or serverless architectures Practical exposure to machine learning plus generative AI models including LLMs SLMs vision models Familiarity with AI frameworks such as RAG LangChain LlamaIndex plus agentic frameworks Hands-on cloud experience within Azure or AWS plus CI/CD tooling and Git Desirable Skills ...

Strong Python development experience within modern data science environments Proven track record building production LLM applications using commercial APIs Deep experience with prompt engineering, RAG architectures and function calling Production experience with cloud platforms including AWS, GCP or Azure Knowledge of containerisation and CI/CD practices Advanced AI Capability ...

experience and API development Experience with data pipelines and vector databases Knowledge of SRE, DevOps, and platform engineering practices Exposure to AI systems, LLMs, RAG, or agent architectures Experience working with UK government or secure environments You'll work alongside expert architects and engineers to deliver complex, high-impact solutions ...

including AI and ML services Solid foundation in software engineering principles for scalable, production-grade systems Experience designing and delivering enterprise AI solutions including RAG-based architectures using vector databases Proven experience delivering full-stack AI or ML systems within enterprise environments Strong understanding of advanced agent architectures, reasoning systems ...

/ML solutions in production Strong programming skills in Python and SQL Experience with classical machine learning and LLMs/generative AI (prompting, RAG, APIs) Solid software engineering fundamentals Experience working with cloud platforms Benefits The successful Senior AI Engineer will receive the following benefits: Salary ...

Python and JavaScript Hands-on experience with backend frameworks and modern frontend frameworks Deep knowledge of Generative AI and agent-based AI frameworks including RAG and orchestration patterns Strong experience working with vector databases and AI-specific data stores Solid understanding of AI and ML models, LLMs and generative ...

outcomes Technical Expertise Generative AI & LLMs Large Language Models (GPT, Claude, Llama, Mistral or similar) Prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) Multimodal AI (text, image, audio, video) Agentic frameworks and orchestration AI/ML Engineering Python, PyTorch, TensorFlow, JAX NLP, deep learning ...

APIs, JSON and spatial query engines (e.g. Apache Spark) Experience with Generative AI technologies including Large Language Models (LLMs), Retrieval Augmented Generation (RAG) and Prompt/Context Engineering Passion for continuous improvement and delivering high-quality solutions The Rewards We want you to love ...

services • Develop applied LLM/NLP systems (conversational AI, embeddings, intent/entity recognition) • Work with PyTorch models deployed in AWS environments • Contribute to RAG, agentic workflows, and orchestration patterns • Collaborate closely with product, engineering, and leadership • Communicate technical decisions clearly to non-technical stakeholders Key details • Salary ...

RESTful APIs, microservices, and event-driven design. DevOps: Strong skills in Git, Azure DevOps, and CI/CD pipeline automation. Desired: Experience with LLMs (RAG, LangChain) , Power Platform, or modern frontend frameworks (React/Angular). Professional Profile Mindset: Entrepreneurial, resourceful, and pragmatic with a "can-do" work ethic. Consulting ...

stakeholders Ability to accurately translate client requirements into technical solutions, and Desirable: NLP experience Experience deploying Generative AI applications, such as chatbots or RAG systems Consultancy or professional services background would be advantageous If you are a Lead Data Scientist who enjoys customer interaction and are looking to advance your ...

have: Strong Python engineering skills for backend services and API integrations. Hands-on experience working with LLMs and related tooling, including: LLMs RAG patterns, vector databases, function calling, and prompt design. Solid experience with Google Cloud Platform, ideally including: Vertex AI, Model Garden, BigQuery, Cloud Run or Cloud Functions Ability ...

patterns, and agile delivery practices Experience with geospatial data, REST APIs, JSON, and spatial engines (e.g., Apache Spark) Experience with Generative AI, including LLMs, RAG, and prompt/context engineering A passion for continuous improvement and delivering high-quality solutions The Rewards We want you to love what you do. ...