8 of 8 Retrieval-Augmented Generation Jobs in West Yorkshire

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 ...

architect/engineer who understands how to construct and integrate hybrid agenticworkflows and toolchains including local agents, SLM/Vector DB's, MCP/RAG/fine-tuning models. 1.Solid engineering experience with CoPilot/Agentic tools (Github CoPilot preferred), across moden cloud native engineering (GCP preferred), with solid grounding ...

Looking For Essential: Strong background in software engineering, architecture or technical delivery Clear pivot into AI, with hands-on understanding of LLMs, agent architectures, RAG and modern AI ecosystems Experience leading client AI or digital transformation engagements Consultancy or professional services background Ability to translate AI capability into commercial value ...

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 ...

Foundry environment. This is a hands-on role focused on building scalable, production-ready AI systems using LLMs, RAG (retrieval augmented generation), vector databases, embeddings and Azure AI services. Key Responsibilities Design and develop LLM-powered applications, AI agents and Copilot solutions Build … optimise RAG pipelines, embeddings and vector search Integrate AI solutions with enterprise systems, APIs and cloud platforms (Azure) Implement secure-by-design AI engineering, monitoring and observability Develop reusable components including prompt libraries, agent frameworks and connectors Prototype, test and improve model performance, reliability and scalability Key Skills Strong experience ...

Applied AI Software Engineer - LangChain, LangGraph, RAG, Knowledge Graphs A high-growth, technology-led scale-up (backed by a global leading organisation) is expanding its engineering capability following a highly successful 2025. As part of significant continued investment, they are hiring a Software Engineer to lead the design and development … next-generation AI products and services across Finance, supporting both internal operations and external platforms. This is an opportunity to work in a modern, cloud-native engineering environment, building intelligent agentic AI systems that can reason, plan and act autonomously. You will take ownership of solutions ...

enterprise-grade AI capabilities. What Youll Be Doing Designing and building Copilot solutions, intelligent agents, and LLM workflows Developing scalable AI components including RAG pipelines, embeddings, and vector search Integrating AI solutions into enterprise systems, APIs, and cloud platforms Conducting rapid prototyping to validate use cases, UX, and model performance … Essential Skills for the AI product developer Proven experience building solutions using LLMs, AI APIs, and Copilot Studio or similar tools Strong understanding of RAG architectures, vector databases, and embeddings Experience with Azure AI and cloud-native development Solid knowledge of secure engineering practices including authentication, data protection, and auditability ...