51 to 75 of 842 Retrieval-Augmented Generation Jobs in the UK

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise AI or ML architecture design, strong cloud ...

Java, including experience with distributed data processing. Leverage enterprise-authorized AI coding assistant tools to improve code quality and delivery speed (e.g., code generation/refactoring, unit tests, documentation), while validating outputs via peer review, automated testing, and secure coding standards; contribute reusable patterns and learnings to improve … Google Bard (or similar). Exposure to LLM application patterns and tooling, including LangChain, retrieval-augmented generation (RAG), and fine-tuning. Experience communicating with and engaging senior leadership and other stakeholders. Preferred: experience building and supporting end-to-end AWS applications, including batch ...

existing business systems and platforms using REST APIs and cloud-native architectures. Build and optimise Retrieval-Augmented Generation (RAG) solutions, embeddings, and vector database implementations. Develop AI Agents and Multi-Agent Systems to automate complex business processes. Apply prompt engineering and context engineering techniques … business stakeholders to drive AI adoption and innovation. Required Experience: Strong background in Generative AI, LLMs, NLP, and AI Engineering. Hands-on experience with RAG, embeddings, and vector databases. Proven experience developing AI Agents and agentic workflows. Proficient in Python, SQL, and API integration. Familiarity with cloud platforms such ...

using Azure AI Foundry, Copilot Studio, Databricks Mosaic AI and MLflow. Building, optimising and evaluating Retrieval-Augmented Generation (RAG) solutions using prompt engineering and embedding models. Designing and deploying AI agents using frameworks including LangChain, LangGraph and AutoGen. Delivering production-ready GenAI applications … Delta Lake, Unity Catalog, DLT and MLflow. Deep knowledge of Large Language Models including GPT, Llama, Claude and Mistral. Experience building and deploying GenAI, RAG and Agentic AI solutions in enterprise environments. Strong programming skills in Python, SQL and/or Scala. Experience with Azure cloud technologies including Azure OpenAI ...

scalable AI solutions. Key responsibilities will include: Leading the technical design and delivery of Generative AI and Machine Learning solutions Designing enterprise-grade LLM, RAG and AI agent architectures Building and integrating conversational, voice-to-text and speech-based AI solutions Developing AI applications using commercial and open-source models … candidates with experience across: Generative AI Large Language Models (LLMs) Machine Learning Deep Learning Retrieval-Augmented Generation (RAG) AI Agents and Agentic AI Multi-agent systems Voice AI Speech-to-text/text-to-speech ElevenLabs AWS Bedrock Amazon SageMaker Google Cloud Platform ...

product) to identify high-impact opportunities for AI-driven automation and intelligent tooling Stay at the forefront of agentic AI research — including LLM orchestration, RAG, function calling, and autonomous code generation — and bring those advances into our platform Mentor engineers across the team on AI-first development practices … with modern LLM orchestration tools, prompt engineering techniques, and AI/ML frameworks Experience with retrieval-augmented generation (RAG), function/tool calling, and evaluation-driven development for AI agents A builder's mentality — you don't just use AI tools, you create autonomous ...

using frontier foundation models (eg Claude, GPT, Gemini family) across use cases including agentic automation, retrieval-augmented generation (RAG), copilots, and multi-modal applications Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architecture and delivery roadmaps Design …/ML or generative AI Proven, hands-on architecture experience with frontier large language models and multi-modal models - including prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design Strong grounding in LLMOps/MLOps: evaluation frameworks, observability, cost and latency optimisation, guardrails, and safe deployment ...

reinforcement learning and LLMs. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertise in data ...

unsupervised learning, reinforcement learningand LLMs. Experience with the latest AI engineering approaches such asprompt engineering, retrieval-augmented generation (RAG)and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertisein data engineering ...

reinforcement learning and LLMs. Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), and agentic AI. Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). Expertise in data ...

learning, reinforcement learning and LLMs. Experience with the latest AI engineering approaches such asprompt engineering, retrieval-augmented generation (RAG),and agentic AI. Strong Python skills with a grounding in software engineering best practices(CI/CD, testing, code reviews etc). Expertisein data engineering ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...