7 of 7 Permanent Retrieval-Augmented Generation Jobs in Avon

Collaborate with multidisciplinary teams to develop Generative AI proof-of-concepts using technologies such as Retrieval-Augmented Generation (RAG) and intelligent agents. Scale successful proof-of-concepts into robust, production-ready solutions. Design and develop full stack applications across both AI-driven and traditional … success. You will work on impactful projects, contribute to the adoption of emerging technologies and play a key role in delivering next-generation AI solutions. Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built ...

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 ...

ambiguous environments and owning projects from concept to deployment. Nice to Have Experience with Retrieval-Augmented Generation (RAG). Knowledge of vector databases and semantic search. Experience with Python alongside TypeScript. Familiarity with AI orchestration frameworks such as LangChain, LangGraph, or similar. Experience with … customers. Technologies You'll Work With Generative AI Artificial Intelligence (AI) AWS TypeScript Large Language Models (LLMs) Rapid Prototyping APIs Data Engineering Vector Databases RAG React/Next.js Node.js Git Docker What Success Looks Like Deliver AI solutions that solve real customer problems. Build production-ready applications in weeks ...

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 ...

custom orchestration frameworks . Integrate leading and self-hosted LLMs with tools, data and external systems using MCP and custom connectors . Implement RAG solutions using vector databases and hybrid retrieval where appropriate. Work across relational, document, key-value and graph databases depending on the problem. Develop prompt ...

products, architecture and future AI roadmap. What you'll do Build AI-powered features within existing C#/.NET products Develop LLM solutions using RAG, agentic workflows and Azure AI Take ideas from proof-of-concept through to production Help shape technical decisions and the wider AI strategy Improve … moved beyond experimenting with AI and can demonstrate something you've genuinely delivered into production. Experience with Azure OpenAI, Azure AI Search, RAG, Semantic Kernel, vector databases or Python-based AI tooling would be particularly valuable. What's in it for you? Up to £70,000 plus bonus Mostly remote ...