Backend Software Engineer — Applied ML & LLM Systems

### About Dwelly Dwelly — a UK-based, AI-enabled lettings and property management platform, that is growing through a roll-up strategy acquiring estate agencies. The company leverages two arms: i) acquiring existing letting agencies, effectively buying its highly sticky, recurring revenue-type landlords portfolios, and then ii) building a top-notch technology to automate tenant management, payments, and post-rental property maintenance. The company seamlessly integrates AI services to automate all business processes within brick-and-mortar real estate agencies, integrating them into a tech-enabled digital letting platform in two months to radically improve the user experiences and increase efficiency of the business. We’re a fast-growing, product-focused company, backed by top-tier investors and led by a team with deep experience in real estate, technology, and operations. ### Position Summary We are looking for a **Backend Engineer with strong applied ML experience** to build production systems that extract, enrich, summarise and structure information from emails, documents and other unstructured data. This is not a pure data science or research role. It is a production engineering role focused on building reliable Python backend services around NLP, retrieval and LLM-powered workflows. You will work on practical problems such as extracting useful information from email correspondence during agency migrations and summarising a client’s full communication history inside their Dwelly profile. The right person is comfortable working with messy real-world data, taking prototypes into production, measuring quality and improving systems through evaluation and feedback loops. ### **What You’ll Do** - Build systems that extract structured data from emails, documents and other unstructured sources. - Enrich migrated client, landlord, tenant and property records with useful information from communication history. - Develop solutions that summarise a client’s full email history and surface the most relevant context inside Dwelly. - Build production NLP / ML-backed backend services that work reliably on messy real-world data. - Improve retrieval and ranking systems using approaches such as RAG, BM25, embeddings, hybrid search and reranking. - Define quality metrics, evaluation datasets and feedback loops for extraction, summarisation and retrieval systems. - Build Python backend services and APIs using frameworks such as FastAPI, Django, Flask or similar. - Integrate ML and LLM workflows into production systems with clear error handling, observability and maintainability. - Work closely with engineering, product and operations teams to turn real business problems into scalable automation systems. ### **What We’re Looking For** - Strong Python backend engineering experience. - Experience with API frameworks such as FastAPI, Django, Flask or similar. - Production experience with NLP, ML, information extraction, retrieval, ranking or summarisation systems. - Ability to take research ideas or prototypes into production. - Strong understanding of evaluation, metrics and quality measurement for ML / LLM systems. - Practical experience with retrieval systems such as RAG, BM25, embeddings, hybrid search or reranking. - Comfortable working with messy, ambiguous or incomplete real-world data. - Ability to build reliable services around ML workflows, including monitoring, testing and failure handling. - Good understanding of LLM limitations, hallucination risks and safe user-facing AI. - Strong ownership mindset and ability to work independently in ambiguous product areas. ### **Nice to Have** - Experience building AI or LLM agents. - Experience with document understanding, email parsing, entity extraction or CRM enrichment. - Experience with LLM evaluation, prompt/version management or human-in-the-loop review workflows. - Experience with vector databases or search infrastructure. - DevOps or CI/CD experience for deploying ML-backed services. - E…