Director of Product Management, Software Mountain View, California,

Mountain View, California, United States

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.
We operate at the cutting edge of Applied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.

The Head of Product Management, Software leads product management for all of Apptronik's on and off-robot software, spanning the autonomy, simulation, software platforms, and cloud deployed tools. You own the software product vision, partnering closely with engineering and research leadership to develop and execute the software roadmap. You’ll build and lead a team of product managers who translate market demands and customer use cases into executable roadmaps.

You are accountable for software products across their full lifecycle, from research and definition through deployment, field operation, and continuous improvement across a fleet.

• Build, lead, and develop the software product management team: hire, coach, and set the standards for how software products are managed.
• Partner with software engineering and research leadership to develop and maintain the software roadmap: scope, sequencing, and priorities across all levels of the stack.
• Define the commercial software strategy, including packaging, pricing enablement, and features that drive recurring revenue (SaaS/RaaS).
• Partner with user experience (UX) leadership to ensure fleet management software is intuitive for enterprise operators.
• Establish roadmap governance, prioritization frameworks, and metrics discipline across the team, holding product managers accountable to customer-connected, outcome-driven roadmaps.
• Define and track portfolio-level product and program health metrics, and represent software product status in executive reviews.
• Partner with engineering to create evaluation, field-testing, and release-readiness criteria, providing oversight on all software go/no-go decisions.
• Own the software product lifecycle beyond launch: over-the-air updates, fleet-wide observability and performance, field-issue resolution, and versioning and deprecation.
• Drive build-versus-buy and in-house-versus-partner decisions across software components and models, weighing capability, cost, time-to-market, and long-term control.
• Lead engagement with software and technology partners and vendors at the product level on requirements, feasibility, integration, and support.
• Align with data collection operations and the ML and AI teams on data strategy: what to collect, why, and the quality bar that feeds model development.
• Align with hardware product leadership across the hardware/software divide so systems are defined, sequenced, and integrated coherently.
• Partner with safety, quality, and compliance teams to ensure software meets applicable standards and that failure modes and field risks are addressed.

• Proven track record building and leading product management teams.
• Deep software product fluency across the lifecycle: from research and definition through deployment, field operation, and continuous improvement, including evaluation and release management.
• Experience with autonomous robots, autonomous vehicles, or similar complex software systems enabling fluency at the hardware/software co-development boundary.
• Working understanding of the robot software stack: autonomy and AI, perception and navigation, simulation, platform and middleware, and the constraints of edge deployment.
• Experience delivering cloud-based software products and services, including the cloud-to-edge architecture that connects a deployed fleet to backend systems.
• A keen eye for build-versus-buy and in-house-versus-partner decisions across components and models.
• Strong analytical skills with metrics discipline for performance tracking and data-driven decision-making.
• Excellent verbal and written communication, translating technical insight into business impact for engineering and…