Interested in this AI Product Manager role at PermitFlow?
Apply Now →Skills & Technologies
About This Role
PermitFlow is redefining how America builds. We’re an applied AI company serving the nation’s builders, tackling one of the largest information challenges in the economy: understanding *what can be built, where, and how*. Our AI agent workforce helps the fastest\-growing construction companies navigate everything from permitting and licensing to inspections and project closeouts – accelerating housing, clean\-energy, and infrastructure development across the country.
Despite being a $1\.6T industry, construction still suffers from massive delays, wasted capital, and lost opportunity. PermitFlow has already delivered unprecedented speed, accuracy, and visibility to over $20B in development, helping contractors reduce compliance time, de\-risk projects, and scale with confidence.
As the U.S. enters a new capex supercycle across data centers, factories, housing, and renewables, joining PermitFlow means building the AI infrastructure at the core of every construction project driving the next wave of reindustrialization.
We’ve raised over $90M, most recently completing our Series B, from top\-tier investors including Accel, Kleiner Perkins, Initialized, Y Combinator, Felicis, and Altos Ventures, with backing from leaders at OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber.
Building the AI Infrastructure for Construction
===================================================
- Construction is one of the largest industries in the world \- and one of the most operationally fragmented.
- Before anything gets built, projects must move through permitting and pre\-construction workflows spread across \~20,000 jurisdictions, each with different rules, systems, and processes.
- The result is a massive bottleneck slowing down housing and infrastructure across the country.
- PermitFlow is rebuilding this layer from the ground up \- using modern software and AI systems to automate and orchestrate permitting end\-to\-end.
- We are still early. The product surface area is expanding rapidly, the workflows are deeply complex, and the opportunity to shape how this industry operates is enormous.
- This is one of those rare moments where product decisions directly influence how the physical world gets built.
Location
------------
- Our HQ is in New York City with a hybrid schedule (Monday, Wednesday and Friday in\-office). We prefer NYC\-based candidates or those open to relocation.
Role Overview
-----------------
- We're hiring a Product Manager, Applied AI to own PermitFlow's core AI infrastructure and workflow agents. This is a role that will require UX and technical acumen to deliver high quality agents in a genuinely complex domain, while also up\-leveling our core agentic infrastructure and data flywheel.
- Submitting a permit means comprehending construction documents, extracting project details, confirming every requirement has been met and often filling in pdf forms. Errors compound across steps and a failed submission adds real cost for our customers as projects slow.
- In this context, you will be asked to deeply familiarize yourself with PermitFlow’s users, customers and use\-cases, so you can develop a blended strategy, supporting single\-shot full automation where possible and utilizing human\-in\-the\-loop patterns where human judgment is still required. This is not an incremental role, we are looking for someone who can have a major impact in how fast construction gets done in America, Canada and beyond.
- The ideal candidate will mix an exceptional history of product delivery with true experience building AI and Agentic infrastructure from the ground up. You ship quickly, instrument everything, hold a high quality bar, and stay close to the users of what you build.
- This role reports directly to our Head of Product. We're hiring at Staff or Senior Staff, with the level based on past experience and interview performance.
What You’ll Do
------------------
You will operate across agent design, evaluation, and operational execution:
- Deliver our core set of workflow agents for permitting, enabling rapid comprehension of construction projects and accurate compliance submissions for permits and inspections
- Define what "reliable enough to submit" means at both the field and submission level, and own the quality bar that gates release
- Own our path to full automation, segmenting use cases and driving to single\-shot submission where accuracy allows
- Design the architecture for assistive use cases, building the agents and tools that empower permit coordinators to move faster where humans\-in\-the\-loop is the best solution
- Work with our operations org to build an evaluation and data flywheel through early testing, golden data set generation, and structured error analysis ahead of submission
- Build a durable design system around our data flywheel, ensuring that users can easily provide feedback on our Agents \& AI products
- Build the internal toolset for testing, error analysis, and hill climbing that every team at PermitFlow uses to ship agentic work
- Serve as the internal applied AI expert for teams coming from more traditional software backgrounds
What We’re Looking For
--------------------------
We're looking for product leaders who have shipped AI into production in domains where accuracy carries real\-world consequences.
- 7\+ years of product management experience, or an equivalent track record in forward deployed engineering, applied research, or operations leadership
- Direct ownership of the quality bar for a shipped AI/Agentic system
- Hands\-on experience building evaluations, including experience with golden data sets, LLM\-as\-judge, human annotation, and online monitoring
- Judgment on when to build an agent and when a simpler product or process change delivers more
- Deep technical fluency and comfortable engaging engineering on technical concepts
- Track record of partnering closely with operations teams and translating operational insight into product
- Ability to operate effectively in ambiguity and create clarity for cross\-functional teams
- High sense of ownership, urgency, and accountability
- Track record of high quality delivery and increased scope across multiple roles
What We Offer
-----------------
- 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)
Closing
-----------
If you’re excited by the opportunity to build AI\-powered products that simplify complex real\-world workflows \- and want to help define a category from the ground up \- we’d love to talk.
Inside PermitFlow: The Team Transforming Construction Permitting
*PermitFlow provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, gender expression, or family status, as protected by applicable law.*
*We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. All employment decisions are based on merit, qualifications, and business needs.*
Compensation Range: $230K \- $300K
Salary Context
This $230K-$300K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $185K across 167 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At PermitFlow, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $217,100 based on 471 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($265K) sits 22% above the category median. Disclosed range: $230K to $300K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
PermitFlow AI Hiring
PermitFlow has 1 open AI role right now. They're hiring across AI Product Manager. Based in New York, NY, US. Compensation range: $300K - $300K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.