Interested in this AI Product Manager role at Homebound Technologies, Inc.?
Apply Now →About This Role
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:
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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:
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- 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:
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- 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.
Compensation Range: $130K \- $180K
Salary Context
This $130K-$180K range is below the median for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Homebound Technologies, Inc., 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 in Demand for This Role
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 $216,175 based on 270 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($155K) sits 28% below the category median. Disclosed range: $130K to $180K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Homebound Technologies, Inc. AI Hiring
Homebound Technologies, Inc. has 1 open AI role right now. They're hiring across AI Product Manager. Based in Santa Rosa, CA, US. Compensation range: $180K - $180K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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
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