AI Engineering Manager

Join PermitFlow as an AI Engineering Manager, where you will lead and scale the engineering team responsible for building the core agentic infrastructure and evaluation systems. This is a builder-leader role that requires both people leadership and technical execution. You will report directly to the VP of Engineering and work closely with the Product Manager, AI. Your responsibilities will include driving your own roadmap, leading and growing the engineering team, owning the technical architecture, and building and scaling the evaluation infrastructure. This is a systems-building role at the foundation of a rapidly growing company in the AI and regulatory space.

• Lead and scale the engineering team responsible for building PermitFlow's core agentic infrastructure and evaluation systems.
• Drive the technical direction and execution planning for the systems that determine whether an AI agent can submit a permit autonomously.
• Partner closely with the Product Manager, AI to define and build the engineering systems that ensure reliability and quality in AI submissions.
• Hands-on familiarity with evaluation infrastructure: golden data sets, LLM-as-judge, human annotation, or online monitoring
• Bonus: experience in workflow-heavy, enterprise SaaS, or infrastructure products
• Strong system design and architecture fundamentals, with judgment on when an agent is the right tool and when a simpler system isn't
• Deep technical fluency: comfortable in code review, architecture review, and model/system tradeoffs
• We’re looking for strong technical leaders who thrive in high-ownership, high-ambiguity environments
• Bonus: exposure to complex regulated environments (construction, logistics, government systems, etc.)
• 5+ years in software engineering, including 1+ year in engineering leadership
• Ability to lead through ambiguity and turn unclear, fast-moving problems into structured execution
• Strong communication skills across technical and non-technical stakeholders, especially product
• High standards for engineering quality, reliability, and performance
• Direct experience building or shipping a production AI/agentic system, not just consuming an API but owning the infrastructure around it