51 to 75 of 93 Retrieval-Augmented Generation Jobs in the UK excluding London

modern vector databases. An understanding of Site Reliability Engineering best practices and Platforms/DevOps best practices. Exposure to AI concepts such as LLMs, RAG, and agent‐based systems (or a strong desire to learn). Experience previously working with central government and an understanding of government ways of working ...

Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents) Experience translating research and experimentation into production systems Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management Hands-on experience ...

business logic * Experience in small, fast-moving teams (startup, scaleup, or consulting) * Strong communication and documentation skills Nice to have: * Experience with LLM workflows (RAG, LangChain, etc.) * Experience in logistics, trade, or compliance data * Experience supporting client-facing or pre-sales conversations To Apply: Please email ...

problem-solving mindset. Strong Python skills Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker ...

problem-solving mindset. Strong Python skills Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker ...

problem-solving mindset. Strong Python skills Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker ...

systems (LangChain/LangGraph or similar) into production Hands-on experience with AI agents, agentic workflows, and multi-step reasoning Experience designing and implementing RAG systems with real-world impact Familiarity with MCP or similar orchestration patterns (FastMCP/FastAPI) Understanding of LLM limitations and trade-offs (hallucination, latency, cost ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

Understanding of DevSecOps, secrets management, enterprise controls, and compliance • Familiarity with Jira and Confluence • GenAI/LLM Fundamentals: Understanding of LLM concepts (prompting, embeddings, RAG, model limitations), and how to apply them safely in engineering workflows • GenAI Tooling & Integration: Experience using and integrating GenAI-assisted tools (e.g., code assistants, chat ...

platforms. Your Skills and Experience Hands on experience building and deploying machine learning models end to end. Experience with LLMs, NLP, conversational AI, RAG pipelines and model fine tuning. Understanding of production grade ML workflows and CI CD principles. Experience building chatbots or NLP driven chat engines used in live ...

delivering solutions at pace. Key Responsibilities Design and build scalable full stack applications Develop and deploy AI-powered solutions including LLM integrations and RAG systems Work closely with stakeholders to translate business needs into technical solutions Lead rapid prototyping and production delivery Contribute to architecture decisions across multiple projects Mentor ...

delivering solutions at pace. Key Responsibilities Design and build scalable full stack applications Develop and deploy AI-powered solutions including LLM integrations and RAG systems Work closely with stakeholders to translate business needs into technical solutions Lead rapid prototyping and production delivery Contribute to architecture decisions across multiple projects Mentor ...

automation Hands-on exposure to tools such as Azure OpenAI, Copilot Studio, or similar platforms Understanding of generative AI approaches, including prompt engineering and RAG Experience integrating enterprise systems via APIs and connectors Familiarity with Power Platform (Power Automate, Power Apps) Awareness of governance, security, and data protection considerations Strong ...

Understanding and hands-on experience with Transformer models and LLMs (e.g., GPT, LLaMA, Mistral, Claude). Skills in fine-tuning, prompt engineering, and building RAG pipelines. Familiarity with Agent Frameworks (LangChain, LlamaIndex, CrewAI, AutoGen). Knowledge of reinforcement learning methods or tools (Q-learning, policy gradients, RLlib). Why Join ...

operating as a senior data leader in a commercially driven environment, with a clear track record of delivery. Key requirements include: Experience using Langchain, RAG systems and Vector databases Proven ability to lead analytics and insight functions, with a bias towards hands on delivery rather than large scale people management. ...

technical audiences. Desirable: Experience with LLMs, prompt engineering, or agent-based AI. Familiarity with AI-assisted development tools. Knowledge of vector search, RAG patterns, or context-management techniques. Sellick Partnership is proud to be an inclusive and accessible recruitment business and we support applications from candidates of all backgrounds ...

client discovery sessions and pre-sales activities, proposal creation, identifying technology and AI opportunities and defining project scope Proven GenAI and LLM expertise, from RAG and fine-tuning to observability, focused on driving measurable business outcomes Advise on technology and architecture decisions, balancing cost, risk, and performance Advising … client-facing proof of concepts Strong knowledge of cloud platforms (Azure, AWS, GCP) and MLOps best practices Experience with Generative AI and LLMs (e.g., RAG, fine-tuning, prompt engineering) Desirable Degree in Business, Computer Science, Engineering, or related field Personal Attributes Strong analytical and strategic thinking skills Excellent communication skills ...

Python. What you'll be doing Designing and building production LLM and GenAI solutions in Python from prototype through architecture to deployment. Implementing advanced RAG pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate … production-ready code. Hands-on experience building and deploying LLM/GenAI solutions in production not just POCs or notebooks. Strong working knowledge of RAG patterns, agentic frameworks, vector databases and embedding models . Familiarity with prompt engineering, LLM evaluation and guardrail design (hallucination mitigation, prompt injection defence, content safety ...

Python. What you'll be doing Designing and building production LLM and GenAI solutions in Python from prototype through architecture to deployment. Implementing advanced RAG pipelines hybrid search, re-ranking, query rewriting, context compression, evaluation and grounding. Working with vector stores such as Azure AI Search, Pinecone, Qdrant, Weaviate … production-ready code. Hands-on experience building and deploying LLM/GenAI solutions in production not just POCs or notebooks. Strong working knowledge of RAG patterns, agentic frameworks, vector databases and embedding models . Familiarity with prompt engineering, LLM evaluation and guardrail design (hallucination mitigation, prompt injection defence, content safety ...

Science, or a related field Interest in AI, machine learning, and modern software development practices Curiosity and eagerness to learn about RAG (Retrieval-Augmented Generation) and other AI applications Strong analytical skills and ability to work collaboratively in a team environment Proactive mindset, ready ...

people actually enjoy being part of. There’s a big push into AI and automation, including: Integrating GenAI into product workflows Exploring LLM and RAG-based features Using AI to improve both user experience and internal processes They’re looking for someone who wants to grow with the business long ...

working in regulated environments or with legal workflows. Thorough understanding of AI technologies used in legal environments (LLMs, NLP, extraction/classification models, summarisation, RAG pipelines, etc.) Hybrid Working Birketts is a flexible business which has embraced a hybrid working model where our colleagues enjoy a mix of home ...

through cutting edge technology, AI and data driven solutions. This is an exciting opportunity to join a growing team focused on building next generation GenAI applications and scalable full stack solutions, working on complex client engagements and shaping enterprise level AI solutions. The Role As a Senior GenAI … LangChain, LangGraph or CrewAI * Experience working with Large Language Models such as OpenAI, Anthropic, Llama or Mistral * Experience with Retrieval Augmented Generation, AI agents or similar GenAI architectures * Experience working with AWS or Azure in production environments * Docker and containerisation experience, Kubernetes desirable * Experience ...

developing technical talent. Advise on internal AI platform strategy and client positioning. Apply modern AI/ML approaches, including LLMs, agent architectures, and RAG techniques, in delivery and practice strategy. Collaborate with stakeholders to translate technical capabilities into practical business impact. What We're Looking For: Essential: Strong background ...

Data & AI platforms (Azure AI, Vertex AI, Databricks, Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications. GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps ...