Staff Product Manager, Physical AI

About Us: Homebound is on a mission to make it possible for anyone, anywhere, to build a home using technology. Created by an experienced team of construction, real estate, design, and technology experts, Homebound is transforming the residential construction industry by improving the costly and inefficient process of building a home. We’ve created an entirely new way to build homes with technology powering every stage from start to finish to provide a seamless experience for our customers. Homeowners across the country can choose where they want to live, select a home plan that’s perfect for them, then personalize and buy it, all online. Homebound has raised $150M in capital from leading venture capitalists like Google, Khosla, Thrive Ventures, and we’re scaling quickly in places like Texas, Colorado and Florida. Come build your future with us. About the Role: As Staff Product Manager, Physical AI, you’ll own the technology that brings AI to the construction site. This is where the digital and physical worlds meet and where most AI products quietly fall apart. Your product surface spans our mobile field app, used by every superintendent, onsite capture including drones, 360° walkthroughs, phone-based capture, and construction schedules that predict slip before it happens and explain why. You don’t need a construction background. You do need to have taken frontier models out of the browser and made them work somewhere messy where inputs are noisy, conditions change daily, and a wrong answer costs a real person a trip to the site. Why This Is a Genuinely Hard Problem: Every home we build generates thousands of photos, plan revisions, inspection results, and schedule events. We have years of structured build data tied to a single shared data platform – longitudinal, real-world construction information that is very difficult to assemble from outside the industry. The hard part isn’t the model. It’s that a jobsite is dusty, half-built, poorly lit, and different every day. Precision matters asymmetrically: a false positive sends a trade partner on a wasted truck roll. Connectivity is unreliable, so some inference has to run on-device. And the people using what you build are on their feet in the sun, wearing gloves, with three minutes to spare. What You’ll Do: • Own the field AI strategy and roadmap. Set the vision and execute end to end across the entire field portfolio – concept through rollout and adoption. • Ship AI into the physical environment. Translate computer vision, VLMs, and agents into products that hold up on an active jobsite, not just in a demo. • Build the quality bar. Establish eval sets and quality frameworks for AI features, design the human-in-the-loop review that makes them safe to ship, and close the flywheel so field corrections make the models better. • Set the direction. Bring a strong, well-formed perspective on where field technology is going, defend it, and use it to shape how Homebound applies new capability to the teams building our homes. • Drive across teams. Move initiatives forward across Construction Operations, Field Operations, and Engineering – independently, without waiting for a playbook. • Define and measure with rigor. Write clear, actionable requirements; prioritize on impact, effort, and durable value; define success metrics and run experiments that systematically improve accuracy, adoption, and field efficiency. What You’ll Bring: • 8+ years of product management, including end-to-end ownership of a complex, technical product at staff-level scope. • A track record of shipping applied AI – computer vision, multimodal, LLM/agent-based, or ML systems – that took meaningful action or made decisions in production. Not chat wrappers, not lightweight integrations. • Technical fluency to operate as a peer to engineers and ML teams: reasoning through system tradeoffs, reading an eval and knowing whether it’s measuring the right thing, and going into the data to answer your own questions. • A real point of view on emerging AI. You follow the frontier closely, you have an opinion about what’s ready to deploy and what isn’t, and you can defend it. • 0 to 1 experience taking a product from concept through launch to real-world adoption, moving fast in ambiguity without heavy process. • Communication that translates cleanly between a superintendent standing on a jobsite, an ML engineer, and the executive team. Our Commitment: We are focused on building a diverse and inclusive workforce. If you’re excited about this role, but do not meet 100% of the qualifications listed above, we encourage you to apply. To apply, please submit an application with your resume on the Career’s page. Homebound is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Homebound considers all qualified applicants in accordance with the San Francisco Fair Chance Ordinance. Our Compensation Philosophy: Our salary ranges are determined by role, level, and location. Please note that the salary range displayed on each job posting may vary by state. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter will share more about the specific salary range for your preferred location during the hiring process. Please note that each job posting includes a general description of any other compensation offered for the position in addition to the salary range displayed on the job posting. You can find information about our benefits here.