Staff Product Manager, Field AI for Construction

Jobicy; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

Homebound is seeking a Staff Product Manager, Physical AI to own the technology that brings AI to the construction site. You will oversee the field AI strategy across our mobile field app, on-site capture, drones, and scheduling, translating frontier models into reliable, real‑world solutions on noisy, dynamic worksites.

Ideal candidates have a track record of deploying AI in production, strong technical fluency, and the ability to defend strategic directions among engineers, ML teams, and

Qualifications

• 8+ years of product management experience with end-to-end ownership of a complex, technical product at staff-level scope.
• Track record shipping applied AI (computer vision, multimodal, LLM/agent-based, or ML systems) that produced real outcomes.
• Technical fluency to reason through system tradeoffs and read eval results intelligently.
• Strong point of view on emerging AI, with defendable judgments about deployable capabilities.

Responsibilities

• Own the field AI strategy and roadmap from concept to rollout and adoption across the field portfolio.
• Translate AI capabilities into products that perform reliably on real job sites (vision, VLMs, agents).
• Define and measure success with rigorous requirements, experiments, and actionable KPIs.
• Lead cross-team collaboration across Construction Operations, Field Operations, and Engineering.

Skills

8+ years of PM experience

Applied AI shipping

Technical fluency

AI frontier understanding

Autonomy in ambiguous environments

Cross-functional communication

Job description

Homebound is seeking a Staff Product Manager, Physical AI to own the technology that brings AI to the construction site. You will oversee the field AI strategy across our mobile field app, on-site capture, drones, and scheduling, translating frontier models into reliable, real‑world solutions on noisy, dynamic worksites.

Ideal candidates have a track record of deploying AI in production, strong technical fluency, and the ability to defend strategic directions among engineers, ML teams, and