Engineering Manager, AI
About The Position
PermitFlow is redefining how America builds by serving the nation’s builders with an applied AI company. Their AI agent workforce helps construction companies navigate permitting, licensing, inspections, and project closeouts, accelerating development. Construction, a $1.6T industry, faces delays and inefficiencies, which PermitFlow addresses by delivering speed, accuracy, and visibility to development projects. The company has raised over $90M, including a Series B round, from prominent investors. PermitFlow is building the AI infrastructure for construction, automating permitting end-to-end with an AI agent workforce that reads documents, extracts details, and drives permits and inspections with minimal human intervention. The company is still in its early stages, actively defining the systems that determine automation levels.
Requirements
- 5+ years in software engineering, including 1+ year in engineering leadership.
- Direct experience building or shipping a production AI/agentic system, owning the infrastructure around it.
- Hands-on familiarity with evaluation infrastructure: golden data sets, LLM-as-judge, human annotation, or online monitoring.
- Strong system design and architecture fundamentals.
- Ability to lead through ambiguity and turn unclear, fast-moving problems into structured execution.
- Deep technical fluency: comfortable in code review, architecture review, and model/system tradeoffs.
- Strong communication skills across technical and non-technical stakeholders, especially product.
- High standards for engineering quality, reliability, and performance.
Nice To Haves
- Experience in workflow-heavy, enterprise SaaS, or infrastructure products.
- Exposure to complex regulated environments (construction, logistics, government systems, etc.).
Responsibilities
- Lead and grow an engineering team building and hardening PermitFlow's agentic infrastructure, raising the bar for ownership, quality, and execution speed.
- Build strong engineering culture through clear expectations, 1:1s, feedback loops, and career development.
- Own the technical architecture behind workflow agents: orchestration, model serving, latency, cost per task, and failure handling at scale.
- Partner with the Product Manager, AI to define "reliable enough to submit" and build engineering systems that gate release against that bar.
- Build and scale evaluation infrastructure: golden data sets, LLM-as-judge pipelines, human annotation tooling, and online monitoring for drift and regression.
- Drive internal tooling for testing, error analysis, and improvement of agentic work.
- Improve system reliability, observability, and engineering efficiency across the AI stack as usage and jurisdiction coverage scale.
- Play a key role in hiring and developing engineers with ML/AI systems depth and future leaders.
Benefits
- Competitive salary and meaningful equity in a high-growth company
- 100% company-paid base medical, dental, and vision coverage for employees + healthcare FSA
- 401(k) savings plan
- Unlimited PTO and paid family leave
- Home office & equipment stipend
- Daily in-office lunch and dinner provided
- Commuter benefits (pre-tax transit and parking)
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What This Job Offers
Job Type
Full-time
Career Level
Manager
Education Level
No Education Listed
