P
PermitFlow
AI Engineering Manager
Skills
Machine LearningAIProduct Manager
1 month ago
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Important information
Contract type:
Permanent
Salary:
$180,000 – $250,000 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
13 September 2026
What they need
- We’re looking for an Engineering Manager, AI to lead and scale the engineering team building PermitFlow’s core agentic infrastructure and evaluation systems
- This is a builder-leader role. You will own both people leadership and technical execution for the systems that decide whether an AI agent can submit a permit on its own, or needs a human in the loop
- You will report directly to our VP of Engineering and partner closely with our Product Manager, AI on where the quality bar sits today and what it takes to move it. Our VP strongly values hands-on technical leadership. The best-fit EMs here are deeply technical, comfortable in the weeds of model behavior and eval design, and just as comfortable running a team
- You will be expected to drive your own roadmap end-to-end from technical direction and execution planning through delivery and measurable accuracy and reliability gains in production, not just shipping features but moving the automation ceiling
- You will operate across systems, people, and execution at scale:
- 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 our workflow agents: orchestration, model serving, latency, cost per task, and failure handling at scale
- Partner with our Product Manager, AI to define what “reliable enough to submit” means, and build the engineering systems that gate release against that bar
- Build and scale our evaluation infrastructure: golden data sets, LLM-as-judge pipelines, human annotation tooling, and online monitoring for drift and regression
- Drive the internal tooling every team at PermitFlow uses to test, error-analyze, and hill-climb agentic work
- Improve system reliability, observability, and engineering efficiency across our AI stack as usage and jurisdiction coverage scale
- Play a key role in hiring and developing engineers with genuine ML/AI systems depth, and future leaders on the team
- This is not a maintenance role - it is a systems-building role at the foundation of a category being created in real time
- PermitFlow sits at the intersection of:
- Fragmented real-world regulatory infrastructure
- High-friction physical economy workflows
- Emerging AI systems capable of automating end-to-end complexity
- The engineering decisions made here directly determine how much of the permitting process can run without a human in the loop, and how fast housing and infrastructure projects move from idea to execution
- This role offers rare leverage: you’ll own both the engineering organization and the core AI infrastructure at an early but rapidly scaling company
Benefits
- Equity packages
- 100% Paid health, dental & vision coverage
- Company issued laptop
- Home office & equipment stipend
- Lunch & Dinner provides via UberEats w/ a fully stocked kitchen
- Commuter benefits
- Team building events
- Unlimited PTO- 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
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