5 of 5 Retrieval-Augmented Generation Jobs in Bristol

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

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 ...

capability. With an established international engineering team of over 50 software and AI engineers , this is an opportunity to help shape the next generation of enterprise AI platforms, intelligent software and agentic systems being deployed into some of the world's most recognised organisations. We're looking … Generative AI GenAI LLMs Large Language Models Foundation Models Agentic AI AI Agents Autonomous Agents Multi-Agent Systems RAG Retrieval Augmented Generation Prompt Engineering AI Evaluation AI Observability AI Governance Responsible AI AI Security Guardrails Model Context Protocol (MCP) Function Calling Tool ...

optimisation, data processing) and cloud platforms (AWS, Azure or GCP). Hands‐on experience with a range of AI concepts such as LLMs, VLMs, RAG, agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Familiarity with ML frameworks (PyTorch, TensorFlow, etc.) and strong proficiency in Python and data structures ...

experience in APIs, integrations and distributed systems Proven experience designing, building and delivering solutions into production environments Experience with AI architecture and patterns, including RAG, tool calling and multi‐agent orchestration Experience building or deploying AI/LLM‐powered solutions and workflows Full‐stack software engineering skills, particularly Python, APIs ...