7 of 7 Retrieval-Augmented Generation Jobs in Lancashire

tool execution. Integrate AI agents with APIs, databases, enterprise systems, and third-party platforms. Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and knowledge repositories. Create secure, scalable, and production-ready AI workflows. Engineer prompts, system instructions, and evaluation frameworks to improve agent … memory, reflection, and tool use. Experience building autonomous AI agents and AI-powered automation solutions. Strong prompt engineering and AI evaluation experience. Experience implementing RAG architectures and semantic search solutions. Software Engineering Strong Python development skills. Experience with JavaScript and/or TypeScript. Experience building and integrating REST APIs. Understanding ...

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 ...

Design, build, and deploy LLM-powered applications and GenAI solutions Develop and optimise prompt engineering strategies for performance and accuracy Implement RAG (Retrieval-Augmented Generation) pipelines using structured and unstructured data Fine-tune and customise foundation models and LLMs where required. Integrate GenAI solutions … software engineering, data science, or machine learning Proven experience building and deploying LLM/Generative AI applications in production environments Hands-on experience with RAG architectures, embeddings, and vector search Experience working with LLM APIs and frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face) Strong understanding of prompt engineering techniques ...

delivering a modern enterprise data platform. This opportunity offers the chance to work on large-scale data initiatives, modern cloud technologies and next-generation analytics capabilities that will support strategic decision-making across the business. The Opportunity You will join a growing data function responsible for building … environments Desirable Experience Microsoft Fabric Power BI development PySpark REST API integrations Lakehouse architectures AI and Machine Learning platforms Retrieval Augmented Generation (RAG) Vector databases Generative AI solutions Power Platform technologies Data transformation or modernisation programmes What We're Looking For We're looking ...

core data science libraries such as pandas, scikit-learn, LangChain, etc. Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. ...

client teams to design, build and deploy AI driven solutions on the platform Translate complex research and business questions into production ready LLM and RAG workflows Debug, optimise and scale LLM applications in real world, client facing environments Build and integrate data pipelines and services across cloud platforms and modern … Your Skills and Experience Strong commercial engineering experience in AI, machine learning or data focused roles Hands on experience with retrieval augmented generation and production LLM workflows Confidence debugging and improving end to end LLM systems in live environments Experience working with modern data ...