LLM Engineer

<p><strong>LLM Engineer – RAG & Knowledge Systems</strong></p><p>Onsite (London, UK) | Hybrid Option Available</p><p>Experience: 3+ years</p><p>AI | Generative AI | Knowledge Systems</p><p><br><br>Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly.<br></p><p>About the Role</p><p>We’re looking for an LLM Engineer to design and implement retrieval-augmented generation (RAG) systems powering next-generation AI applications.</p><p>You’ll work on intelligent systems that combine large language models, retrieval pipelines, and enterprise knowledge sources to create AI copilots, assistants, and advanced search experiences used in real-world environments.</p><p><br></p><p>This role is ideal for engineers who enjoy working on the cutting edge of:</p><ul><li>generative AI</li><li>semantic search</li><li>retrieval systems</li><li>and production-grade LLM applications.</li></ul><p><br></p><p>What You’ll Be Working On</p><ul><li>AI copilots and intelligent assistants</li><li>Enterprise knowledge and document systems</li><li>Retrieval pipelines combining:</li><li>embeddings</li><li>vector databases</li><li>LLM inference</li><li>Production-grade generative AI workflows</li></ul><p><br></p><p>Key Responsibilities</p><ul><li>Design and implement RAG architectures and retrieval pipelines</li><li>Develop systems using LLMs, embeddings, and vector databases</li><li>Optimise relevance, latency, and response quality of AI systems</li><li>Integrate AI services into backend platforms and APIs</li><li>Build evaluation and testing frameworks for retrieval quality</li><li>Collaborate with AI, backend, and product teams to deliver production-ready systems</li></ul><p><br></p><p>Required Skills & Experience</p><ul><li>3+ years experience in AI, backend, or machine learning engineering</li><li>Strong Python programming skills</li><li>Experience with LangChain, LlamaIndex, or similar frameworks</li><li>Experience working with vector databases (Pinecone, Weaviate, FAISS, ChromaDB, etc.)</li><li>Understanding of embeddings, semantic search, and LLM workflows</li><li>Experience building or deploying AI systems into production</li></ul><p><br></p><p>Nice to Have</p><ul><li>Experience with OpenAI APIs or open-source LLMs</li><li>Familiarity with prompt engineering and context optimisation</li><li>Experience with cloud platforms (AWS, Azure, or GCP)</li><li>Exposure to knowledge management or enterprise AI systems</li></ul><p><br></p><p>Why Join? xwzovoh </p><ul><li>Work on cutting-edge LLM and generative AI systems</li><li>Be part of one of the fastest-growing areas in AI engineering</li><li>Onsite collaboration in London with hybrid flexibility</li><li>Opportunity to build AI systems used in real-world production environments</li></ul><p><br></p><p>If you’re passionate about LLMs, semantic retrieval, and building intelligent AI systems, we’d love to hear from you.</p><p><br></p><p>Apply via XpertDirect — connecting companies with advanced AI engineering talent.</p>