51 to 71 of 71 Retrieval-Augmented Generation Jobs in the UK excluding London

Generative AI solutions using Azure AI Foundry, Azure OpenAI and Azure ML. Collaborate with clients to define use cases and translate business needs into technical solutions. Building and implementing RAG pipelines and fine-tuning models. Presenting technical concepts to both technical and non-technical stakeholders. Contributing to agile delivery processes and sharing knowledge through workshops and demos. To be successful More ❯

Generative AI solutions using Azure AI Foundry, Azure OpenAI and Azure ML. Collaborate with clients to define use cases and translate business needs into technical solutions. Building and implementing RAG pipelines and fine-tuning models. Presenting technical concepts to both technical and non-technical stakeholders. Contributing to agile delivery processes and sharing knowledge through workshops and demos. To be successful More ❯

SINDy) Working knowledge of cell biology. Experience with Python, C, R or related scientific computing languages. Preferred Qualifications - Experience working with causal representation learning Experience with RAG (retrieval-augmented generation) and GraphRAG a big plus Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of More ❯

to public and private sector clients.Details- Proven experience building Agentic AI systems (e.g. autonomous agents, multi-agent orchestration, tool use, memory, planning) Strong hands-on skills in Python, LLMs, RAG, and LangChain or similar frameworks Deep understanding of GCP services: Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc. Experience with batch and real-time data pipelines Familiarity with AI 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 ❯

and recommend relevant advancements Requirements : 2-5+ years experience in an AI-focused enterprise/start-up Strong Python skills Strong practical experience in LLM concepts (context engineering, RAG, tool calling, workflows, multi-agent systems, MCP) Hands-on experience with frameworks like LangChain, Llamaindex, etc., vector stores, LLM APIs (e.g. OpenAI API, Anthropic API), and building MCP servers/ More ❯

teams to align requirements for application development within a graph and semantic framework. Contribute to data modelling and architecture to support reporting, UI development, and AI-driven tools (LLMs, RAG queries, etc.). Work within an Agile delivery framework to drive business value and measurable impact. Develop and present business-impacting deliverables to senior stakeholders and executive leadership. Track adoption More ❯

hands-on experience in API design and cloud architecture (Azure). Experience with Excel add-ins or Office JavaScript APIs is highly desirable. Exposure to vectorization, RAG (Retrieval-Augmented Generation), or AI-driven data handling frameworks is a big plus. Bonus: Background or interest in commercial real estate technology. Self-starter with excellent communication More ❯

hands-on experience in API design and cloud architecture (Azure). Experience with Excel add-ins or Office JavaScript APIs is highly desirable. Exposure to vectorization, RAG (Retrieval-Augmented Generation), or AI-driven data handling frameworks is a big plus. Bonus: Background or interest in commercial real estate technology. Self-starter with excellent communication More ❯

our users. Main Duties and Responsibilities Data & Retrieval Build robust ingestion pipelines for PDFs/Word/Excel/Audio/JSON and semi-structured sources. Design RAG systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate). … Vault, private networking. Add observability: tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts. Apply evaluation & QA: regression suites, offline eval sets/golden data, RAG evals (faithfulness, answer relevance, citation correctness), A/B tests, win-rate testing. Ensure reliability: rate-limit handling, retries/backoff, idempotency, circuit breakers, caching (e.g., Redis/semantic cache More ❯

LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to deliver production ready, scalable AI solutions Implement generative AI and advanced analytics features, including embeddings, retrieval-augmented generation, and building AI agents and chat-based solutions. Write clean, testable, and well-documented code using modern engineering practices (unit testing, code reviews, API More ❯

a successful, the ideal Senior Software Engineer candidate will have: · A deep experience of working on backend projects with Typescript and Node · Strong experience with Python/LLMs and RAG · Experience of building products that customers will love to use · Experience of working in a small team and getting things done If you are an ambitious Senior Software Engineer hit More ❯

goes beyond static models to deliver autonomous, measurable business impact. To accelerate this capability, we're hiring a Senior Generative AI Engineer to design, build, and deploy next-generation AI ecosystems for global enterprises. You'll … join a hybrid London team (two days a week on-site) with strong flexibility for remote work. Your Role Design, build, and deploy generative AI systems (LLMs, retrieval-augmented architectures, embedding pipelines, agents) from prototype to production. Lead the full ML lifecycle: data extraction, modelling, fine-tuning, training, inference, deployment, and monitoring. Collaborate with product, engineering … engineers and raise the overall technical bar of the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. 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 ❯

The role The role is building AI applications based on LLM and models such as GPT and BERT You'll make use of Python programming, Pyspark, tensorflow, HuggingFace, LangChain, RAG techniques, interfacing with diverse data sets. Cloud data platforms and a diverse set of tools for AI app deployment. The opportunity Work at the forefront of the industry. It's … on experience in a commercial environment, working on AI/ML applications Multi cloud exposure (Azure/AWS/GCP) . Some of the following - Pytorch, GPT/BERT, RAG, Apache Airflow, Power Automate, Azure logic apps, RPA/Zapier, HuggingFace, LangChain... Background in Data Science or Software Engineering The values and ethos of this business Innovation with real purpose More ❯

environment. What You’ll Do Train and fine-tune LLMs and ML models using standardised experiments and high-quality data. Build and improve LLM-based systems for low-latency RAG systems, intent detection, call scoring, and email classification. Support real-time inference infrastructure with ultra-low latency and detailed monitoring. Create and maintain evaluation datasets to test safety, prompt following … and drive to improve model performance. Why Join Us Work on real applied LLMs from training to deployment. Collaborate with an ambitious, research-informed team. Shape the next generation of AI-driven communication tools. More ❯

AI Product Manager (RAG experience essential) - £650 per day - Outside IR35 Are you excited by the challenge of turning cutting-edge AI into real, working products? We’re looking for an experienced Product Manager to help define, deliver, and scale AI Minimum Viable Products (MVPs) for a major enterprise client - applying RAG, LLMs, and generative AI to automate workflows, enhance … high-value AI opportunities and shape product roadmaps. Translate requirements into actionable user stories and acceptance criteria for engineering and data teams. Collaborate closely with teams building solutions using RAG pipelines, LLMs, embeddings, and API integrations. Define and track KPIs such as accuracy, latency, adoption, and ROI — iterating based on real-world feedback. Ensure all solutions meet enterprise-level standards … About You Proven experience as a Product Manager in AI, data, or enterprise technology environments. Hands-on exposure to AI MVPs, LLM applications, or applied ML use cases (e.g. RAG, copilots, generative search). Strong technical grounding in vector search, embeddings, APIs, data pipelines, and prompt design. Skilled in navigating complex enterprise settings and managing senior stakeholders. Pragmatic and delivery More ❯

An exciting opportunity to join a small, high-impact AI team building an internal AI Platform that powers the next generation of intelligent products and services. You’ll work on cutting-edge AI infrastructure, collaborate with experienced platform engineers, and make a real impact on how AI innovation scales across the organization. What you’ll be doing: Building … managing LLMOps tools such as LiteLLM, Langflow, and Langfuse Implementing observability with Prometheus, Grafana, and Loki Managing infrastructure through Terraform, ArgoCD, and GitHub Actions Supporting internal AI applications including RAG, document processing, and internal AI assistants What you’ll need: 2–4 years in Platform or DevOps Engineering (Azure preferred) Strong experience with Kubernetes, Docker, and Terraform Programming or scripting More ❯

We’re looking for a DevOps Engineer who’s excited about building the infrastructure behind next-generation AI products. You’ll join a small, experienced team developing an internal Kubernetes-based platform that enables AI innovation across the organisation automating everything from deployments to observability, and helping developers build smarter applications with confidence. What you’ll be doing … environments Managing Infrastructure as Code with Terraform and improving GitOps workflows (ArgoCD/GitHub Actions) Building observability and monitoring stacks using Prometheus, Grafana, and Loki Supporting AI workloads (LLMs, RAG, and document processing applications) running on Kubernetes Automating platform operations with Python, Go, and shell scripting Implementing security guardrails, PII compliance tooling, and best practices for production AI systems What More ❯

user-focused AI services across our business. What You'll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation methods that can … LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches for GenAI environments. Knowledge of modern AI architectures (RAG pipelines, embeddings, API integrations such as OpenAI, Azure OpenAI, Anthropic). Experience designing and implementing structured test regimes in fast-evolving contexts. Excellent communication and facilitation skills, engaging both technical More ❯

AI platform. We're building a new team in London and hiring for a Senior Forward Deployed Engineer to help enterprise clients unlock the full power of LLM + RAG technology What you'll do Work directly with enterprise clients to turn business needs into live AI use cases Lead proof of concepts (pre-sales) and guide customers through onboarding … directly with enterprise customers (consulting, workshops, exec comms) Development skills are desirable (Python/JavaScript/TypeScript) for prototypes and integrations Strong understanding of AI/LLM concepts (prompting, RAG) Track record in digital experience or enterprise SaaS Highly desirable but not a showstopper A significant background in the Digital Experience Platform (DXP) On offer Hybrid model - 3 days per More ❯