About this role.
Homebound is seeking a Senior Product Manager to lead its Field AI portfolio for residential construction teams. The role owns strategy, roadmap, execution, evaluation, rollout, and success metrics for mobile, computer vision, multimodal AI, agentic, and automated data-capture products used on active jobsites. This senior individual contributor will work independently across Construction Operations, Field Operations, and Engineering while traveling to Texas monthly to embed with field users. The ideal candidate has 5+ years of product management experience and has shipped production applied-AI products that drive real-world decisions or actions. Strong technical judgment, 0-to-1 product delivery, field research, and executive-to-operator communication are central to success.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Sample interview questions
I would describe the user workflow and the operational decision or action the system supported, then explain how I validated feasibility, defined quality thresholds, and staged the rollout. I would quantify outcomes such as accuracy, task-completion time, adoption, exception rate, and business impact, while also discussing what changed after field feedback.
I would begin with the workflow, decision risk, input quality, latency needs, and cost of error rather than selecting technology first. I would compare approaches through a small prototype and evaluation set, favoring the simplest reliable solution and adding human review where uncertainty or safety consequences are high.
I would build a representative dataset across jobsite conditions, device types, trades, lighting, and edge cases, with clear ground truth and segmented performance reporting. The framework would include offline quality metrics, production monitoring, confidence thresholds, feedback capture, and defined escalation or fallback paths when the model is uncertain.
I would make the tradeoffs explicit through a shared problem statement, user evidence, expected impact, technical constraints, and measurable success criteria. I would use a phased plan to deliver an initial high-value workflow, create regular decision forums, and keep stakeholders aligned through transparent progress and outcome reporting.
I would spend the first phase embedding with field users and reviewing current workflows, product telemetry, model performance, and roadmap assumptions. Next, I would identify the highest-value opportunities and reliability gaps, align on a prioritized roadmap and evaluation standards, and launch a focused pilot with clear adoption and efficiency targets.
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 diving into the data to answer your own questions.
A self-starter and independent operator who thrives in ambiguity, moves quickly, and drives outcomes cross-functionally without heavy process.
A genuine thought leader in emerging AI – you follow the frontier closely and have a point of view on how to apply it.
0→1 product building: hands-on experience taking a product from concept through launch to real-world adoption.
Exceptional communication skills and the ability to translate seamlessly between field needs, technical teams, and executive leadership.
Willingness to travel to Texas monthly to work shoulder-to-shoulder with our field teams.
Interest in construction and the built environment is a plus; no prior industry experience required, but an expectation to learn the domain rapidly.
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.
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