8 of 8 Retrieval-Augmented Generation Jobs in Hampshire

libraries such as TensorFlow or PyTorch. Experience working with LLMs (Gemini), prompt engineering, and reinforcement learning from human feedback (RLHF). Experience with LangChain for building LLM applications with RAG pipelines and agent workflows. Practical understanding of vector search, embeddings, and retrieval-augmented generation (RAG). Experience building and deploying machine learning models into More ❯

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 ❯

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 ❯

ll do: 💡 Contribute to the development of DDX — design, build, and scale intelligent systems 💡 Work on AI-driven features: LLMs, retrieval-augmented generation (RAG), and AI agents 💡 Build APIs, data pipelines, and backend components (mainly Python, FastAPI/Flask) 💡 Deploy microservice-friendly solutions, often in containerised setups (e.g. Docker) 💡 Work with ElasticSearch, Weaviate, Pinecone 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 ❯

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 ❯

growth startups (Monzo, N26, Personio). Demonstrable ability in building and leading high-calibre engineering teams . Experience leading engineering teams working on Generative AI (Prompt Engineering, Fine Tuning, RAG) Competencies: Understanding Technical Requirements with a Focus on Quality: Translate product requirements into squad plans and capacity, while also having a keen eye for ensuring high coding standards, maintainability, and More ❯