Senior Product Manager Field AI positions focus on delivering results in their domain. This page aggregates open Senior Product Manager Field AI roles and what employers typically expect.
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 Senior Product Manager - Field AI, you will own the forward-looking technology that brings AI to the teams building our homes. This is where the physical and digital worlds meet: your users are the Superintendents and Direct Construction Operators (DCOs) on the jobsite, and your product surface spans our mobile application, advanced onsite AI tools, automated data capture, and probabilistic construction schedules with insight analysis. This is a role for a thought leader in applied AI. We are looking for someone with a strong point of view on how emerging technologies - computer vision, agents, LLMs, and multimodal models - can be applied in a physical, unstructured environment to make our field teams faster, more accurate, and more effective. You don't need a construction background (though genuine curiosity about the built world is a plus), but you do need real experience translating frontier AI into products that work in the real world, outside the browser. You'll own the roadmap, execution, and success metrics for the field AI portfolio, and you'll operate as an independent, cross-functional force connecting Construction Operations, Field Operations, and Engineering. WHAT YOU'LL DO: - Own the field AI strategy and roadmap: Set the vision and execute end-to-end across the entirety of our field portfolio - from concept to rollout. - Bring AI into the physical environment: Translate the capabilities of computer vision, multimodal models, and agents into products that operate reliably on an active jobsite, where inputs are messy and conditions change daily. - Lead as a thought partner: Bring a strong, well-formed perspective on where field technology is going, and use it to shape how Homebound applies new technologies to the teams building our homes. - Embed with the field: Travel to Texas monthly to work directly with Superintendents and DCOs, run trainings, drive rollouts, and build the tight feedback loops that make field products actually stick. - Drive progress across teams: Operate independently and move initiatives forward across Construction Operations, Operations, and Engineering without waiting for a playbook. - Define product with rigor: Write clear, actionable requirements, establish evaluation and quality frameworks for AI features, and prioritize based on impact, effort, and long-term value. - Measure what matters: Define success metrics and run experiments to systematically improve accuracy, adoption, and field efficiency. WHAT YOU'LL BRING: - 5+ years of product management experience, including ownership of a complex, technical product. - A track record of shipping applied AI products - computer vision, multimodal, LLM/agent-based, or ML systems - that took meaningful action or made decisions in production, not just chat wrappers or lightweight integrations. - Demonstrated experience applying technology in the physical world or in traditionally non-tech, unstructured environments (a strong plus). - Strong technical fluency - comfortable operating alongside engineers and ML teams as peers, reasoning through system tradeoffs, reading evaluations, and d…