4 of 4 Retrieval-Augmented Generation Jobs in West Yorkshire

and n8n. Apply Large Language Models (LLMs) to real-world challenges like email triage, document parsing, and data enrichment. Implement retrieval-augmented generation (RAG) to power internal AI assistants with trusted business knowledge. Rapidly prototype and iterate on Proofs of Concept to test ideas and gather user feedback early. Use AI agents to automate … Experience using Python, OpenAI, LangChain, and vector databases. Familiarity with automation platforms like n8n, Zapier, or similar. Solid understanding of retrieval-augmented generation (RAG) methods. Strong problem-solving skills and the ability to design practical AI solutions with business outcomes in mind. Excellent communication skills – able to work cross-functionally and explain technical concepts More ❯

object detection (e.g. MobileNet, YOLO). Either way, we’re looking for someone who can help our app understand what the visitor is looking at – reliably and at scale. RAG Systems, Data Pipelines & Internal Agents: You'll design the data pipelines that power our AI features, including retrieval-augmented generation (RAG), internal LLM-based More ❯

trajectory forecasted for 2025. Our platform is already trusted by nearly half of the top 50 financial institutions globally. The Technology At the core of our platform is a RAG-based architecture, purpose-built for finance. It’s designed to replicate the kind of deep reasoning you see in leading models like OpenAI’s o1—capable of parsing nuanced questions … frameworks (Python, React, TypeScript, etc.) and can build production-ready systems end-to-end Are excited by AI-native product design and have experience working with or around LLMs, RAG, or agent-like architectures Love talking to users and solving real business problems—not just coding in a vacuum Bring an entrepreneurial mindset, with an eye toward growing into a More ❯

trajectory forecasted for 2025. Our platform is already trusted by nearly half of the top 50 financial institutions globally. The Technology At the core of our platform is a RAG-based architecture, purpose-built for finance. It’s designed to replicate the kind of deep reasoning you see in leading models like OpenAI’s o1—capable of parsing nuanced questions … frameworks (Python, React, TypeScript, etc.) and can build production-ready systems end-to-end Are excited by AI-native product design and have experience working with or around LLMs, RAG, or agent-like architectures Love talking to users and solving real business problems—not just coding in a vacuum Bring an entrepreneurial mindset, with an eye toward growing into a More ❯