Sr. Technical Product Manager (Site Intelligence & Enterprise AI)

The Role

This is a builder + visionary role with a strong bias toward action. You will own the development of enterprise intelligence capabilities — starting from a blank page, validating fast, and shipping things that create real behavior change for construction teams.

You won't wait for customers to tell you what they need. You'll form a strong point of view on how construction operations should work in an AI-native world, build toward it, and bring customers along.

We're in an active fundraising year — speed of validation matters.

What You'll Own

1. Daily Scanning Intelligence (Your Day-One Focus) We're rolling out drone-in-the-box technology — autonomous drones that scan sites daily or multiple times per day. Your first mission is to extract meaningful business value from this continuous data stream and package it into testable enterprise prototypes.

• Define what "intelligence" looks like from daily drone scans

• Build fast, scrappy prototypes yourself — not just specs for engineers

• Validate with enterprise customers quickly and cheaply

2. Enterprise Intelligence Design how data scales into decisions across projects, portfolios, and enterprises.

• Build cross-project data models and aggregated analytics

• Define decision systems — not just dashboards

• Enable executive-level users to act on real-time insight

3. AI & Automation Apply Computer Vision and Machine Learning (not just LLMs) to automate site analysis and document understanding.

• Prototype solutions hands-on using available AI tooling

• Ship only what delivers real, measurable efficiency gains

• Balance fast experimentation with production reliability

4. Ecosystem & Data Connect GIS, CAD, and construction systems into a coherent data foundation.

• Build pipelines that feed analytics and AI models

• Ensure every integration drives automation or decision-making

• Work with operational teams on data acquisition workflows

What the First 90 Days Look Like

• Get deep into the drone-in-the-box project and the daily scanning data

• Deliver 2–3 enterprise prototypes (these can be simple — an analytics export pushed into a client's PM tool counts)

• Go from hypothesis → prototype → customer validation, fast

• Set the direction for a production-ready solution in Q2

Who You Are

Must-have:

• 5+ years in enterprise B2B product management

• Hands-on experience with Computer Vision and/or Machine Learning products — not just LLM wrappers or AI-assisted workflows

• Proven ability to build prototypes yourself, not just direct engineers

• Experience in a technically complex, physical-world domain (construction, GIS, industrial, marine, energy, etc.)

• Near-native English — you'll be communicating regularly with US-based enterprise clients and leadership

• Strong systems thinker with high autonomy and low need for process

Nice-to-have:

• Direct construction industry background — as a PM, architect, engineer, surveyor, or similar

• Hands-on experience with CAD, Revit, GIS, or geospatial tools

• Familiarity with drone data, orthophotos, or terrain modeling

The mindset we're hiring for: You're a visionary and a decision-maker — not a moderator. You form strong opinions, move fast, convince others, and build before it's obvious. Think "mad scientist with good judgment."

Compensation & Benefits

• Competitive base salary

• Unlimited PTO

• Private health insurance

• Wellness and learning programs

• High autonomy, low process

TraceAir - #1 Platform for the top US Homebuilders and Land Developers.

We combine software, drone data, and geospatial analytics to streamline construction workflows, reduce costs, and improve decision-making across site development, land acquisition, and market analysis. Trusted by leading homebuilders, TraceAir delivers practical, end-to-end solutions that drive efficiency, transparency, and profitability. Join TraceAir and help shape the future of construction technology, delivering measurable value to customers at scale.

Our next step is turning that raw data into automated intelligence at scale: across projects, portfolios, and entire enterprises. This means moving from "here's your site data" to "here's what you should do about it" — automatically, continuously, and without manual interpretation.