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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 a core early member of the agentic infrastructure team, responsible for building the systems that power AI-driven automation across Dwelly's operations. The role bridges engineering and operations, turning complex workflows into reliable production systems.
Key responsibilities include:
**Agentic Infrastructure**: Design and build core primitives for agentic systems—memory, context management, tool-calling, orchestration, and feedback loops. Move from one-off AI solutions toward reusable infrastructure that enables rapid, reliable workflow automation as the company scales.
**Evaluation & Observability**: Build evaluation frameworks to understand agent performance and failure modes. Make testing, tracing, debugging, and evaluating AI systems as fundamental as unit testing in traditional software. Develop systems for confident pre-production assessment.
**Agentic Development**: Push forward 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. Use agentic workflows in your own development.
**Orchestration**: Design systems where specialized agents, tools, deterministic software, and humans work together effectively. Develop judgment about when to use LLMs, traditional software, or coordinated multi-agent approaches.
**Operational Automation**: Act as the bridge between complex operational workflows and engineering. Work closely with operational and product teams to identify high-leverage automation opportunities and turn them into production systems.
**Architectural Influence**: Help define architectural patterns for agentic systems as the company scales. You'll have significant influence over technical approach, tooling, and engineering standards.
Required qualifications: Strong software engineering background with experience delivering complex systems end-to-end. Hands-on production experience building AI or 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 and ability to decompose complex tasks across agents. Experience with TypeScript/Node.js or strong Python background with willingness to apply it in TypeScript. High autonomy, ownership, and comfort with ambiguity. Strong product judgment connecting technical decisions to business outcomes. Fluent English and startup mentality.
