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Dwelly is building an AI operating system for residential lettings, operating over 15,000 properties and $470M in GMV as one of the UK's ten largest lettings operators. The company has raised $263M and is backed by top-tier investors.
You will be an early core member of the AI engineering team, responsible for designing and building the agentic infrastructure that powers automation across Dwelly's operations. The role bridges complex operational workflows with engineering, turning manual processes into reliable AI-driven systems as the company scales through agency acquisitions.
Key responsibilities include:
**Agentic Infrastructure**: Design core primitives including memory, context management, tool-calling, orchestration, and feedback loops. Move from one-off AI solutions toward reusable infrastructure enabling rapid, reliable workflow automation.
**Evaluation & Observability**: Build evaluation frameworks to understand agent performance and failure modes. Establish testing, tracing, debugging, and evaluation as fundamental engineering practices for AI systems.
**Agentic Development**: Push how LLMs are used to build software. Create workflows where coding agents and specialized subagents explore repositories, implement changes, review architecture, and iterate with minimal human coordination.
**Orchestration**: Design systems where specialized agents, tools, deterministic software, and humans work together effectively. Make architectural decisions about when to use LLMs versus traditional software.
**Operational Automation**: Act as bridge between operational teams and engineering. Understand real workflows across acquired agencies and turn high-leverage opportunities into production systems.
**Architectural Influence**: Help define architectural patterns for agentic systems as the company scales, with significant influence over technical approach and engineering standards.
Required qualifications: Strong software engineering background with experience delivering complex systems end-to-end. Hands-on production experience building AI/agentic systems. Deep understanding of agents, tool use, structured outputs, context management, orchestration, evaluation, and feedback loops. Advanced practical use of modern LLMs with understanding of building reliable workflows around probabilistic systems. Experience with coding agents and agentic development workflows. Strong architectural judgment. TypeScript/Node.js experience or strong Python background with willingness to apply it in TypeScript. High autonomy, ownership, and comfort with ambiguity. Strong product judgment and communication skills.
