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NEXTMOVEFDE careers · United States

AI Product Engineer

Technologies

RedwoodJS · React · TypeScript · Node.js · GraphQL · PostgreSQL · AWS · LLMs · vector databases · RAG

About GovWell

AI-native operating system for small and mid-sized US local governments, automating permitting, licensing, code enforcement, zoning and inspections to replace legacy vendors.

Series A · 50–100 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Production engineering · Evidence for this classification:

🏛️ About GovWell We the people — and the taxpayers — deserve good government. Yet today, interacting with government services is often frustrating and inefficient. GovWell is building the AI operating system transforming how governments serve communities, starting with local agencies. GovWell replaces legacy software for municipalities and counties, empowering public servants to radically streamline public services and cut internal processing time for permits and licenses by up to 95%. Founded in 2023, GovWell powers 5,000+ mission-critical processes for agencies in 35+ states serving millions of residents. The company has raised $35M in funding from Insight Partners, Work-Bench, and Bienville Capital, and the team works in person at GovWell HQ in New York City. Read more about our founding story in TechCrunch. 🌟 Role overview GovWell already has AI in production doing real work
More from the job description

🏛️ About GovWell We the people — and the taxpayers — deserve good government. Yet today, interacting with government services is often frustrating and inefficient. GovWell is building the AI operating system transforming how governments serve communities, starting with local agencies. GovWell replaces legacy software for municipalities and counties, empowering public servants to radically streamline public services and cut internal processing time for permits and licenses by up to 95%. Founded in 2023, GovWell powers 5,000+ mission-critical processes for agencies in 35+ states serving millions of residents. The company has raised $35M in funding from Insight Partners, Work-Bench, and Bienville Capital, and the team works in person at GovWell HQ in New York City. Read more about our founding story in TechCrunch. 🌟 Role overview GovWell already has AI in production doing real work inside government: Our AI AutoCheck reviews permit applications against local building codes, and our AI Community Assistant automatically answers resident and staff questions about permitting and licensing. Both are live, both are improving fast, and both are still early enough that the engineers who join this team now will define the kind of impact that AI can have at GovWell. GovWell is hiring AI Product Engineers to grow our AI product line beyond AutoCheck and the AI Community Assistant. You' [... source excerpt omitted ...] onal autonomy and ownership over your work. 💻 What you’ll do Expand AI AutoCheck's coverage and accuracy — last quarter it addressed nearly thousands of applications across 100+ customers with a 4.4/5 govstaff satisfaction score. Closing the gap between "good today" and "reviewers trust it completely" is real, immediate work. Improve AI Community Assistant's retrieval grounding and evaluation infrastructure so its answers hold up as we expand to more jurisdictions, more languages, and more question types. Use real production usage data — not synthetic benchmarks — to decide what to fix next; both products already have paying customers depending on the answers being right. Ex [... source excerpt omitted ...] ck and AI Community Assistant. Nothing here is locked in, and you'll have real input into what gets built next rather than executing a roadmap someone else already wrote. Ship to production quickly and iterate based on what actually happens once real government staff and residents use it. 🧠 Who you are You've built with LLMs beyond prompt-wrapping — retrieval-augmented generation, evaluation harnesses, or reliability/hallucination mitigation in a system real users depended on. You know the difference between a demo that impresses in a meeting and a system reliable enough that a government reviewer will actually trust its output — and you're energized by closing that gap, not ju

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