Staff Software Engineer

What You'll Do

• Own problem areas, not just features—define the technical direction for a domain spanning multiple product surfaces, and carry it from ambiguity through architecture to shipped, iterated-on product
• Turn unstructured permitting documents, city regulations, and jurisdiction workflows into fast, reliable product experiences, with AI at the core of how the product works
• Build with AI agents as a daily practice—directing, reviewing, and shipping agent-driven work at high velocity while owning the quality bar
• Multiply the engineers around you: set technical direction others build within, mentor senior engineers toward larger scope, and make the whole team faster through the systems, standards, and abstractions you create

Who You Are

• Thrive in ambiguity—you'd rather define the right problem than execute a spec, and you're energized rather than paralyzed when the path isn't laid out
• Are product-minded: you care whether the thing you built actually solved the customer's problem, and you'll talk to users to find out
• Have strong opinions about quality and velocity and don't treat them as a tradeoff — you look for the tools, abstractions, and processes that buy both
• Default to ownership at organizational scale: when something is broken or missing—a system, a process, a gap between teams—your instinct is to fix it, and you don't need permission or a mandate to start

Need to Have

• 8+ years of software engineering experience
• Track record of owning a significant technical domain end-to-end: from "this is somebody's problem" through architecture, delivery, and production ownership, including the unglamorous parts
• Fluency in modern full-stack development—we use TypeScript, React, and Google Cloud; you don't need our exact stack, but you should be productive with something similar
• Real experience building with AI coding agents and LLM-powered features—not just autocomplete; you've shipped work where agents did substantial implementation under your direction
• Able to architect durable systems while making pragmatic tradeoffs
• Experience mentoring engineers or setting technical direction that other engineers built within

Nice to Have

• Experience in construction tech, govtech, proptech, or another domain where the hard part is messy real-world documents and processes
• Experience designing evals or otherwise making LLM-powered features reliable in production
• Experience as the most senior engineer in a domain—being the person others escalated to when nobody knew the answer
• Startup experience at the stage where you helped build the team, not just the product