Lead product for robotics and autonomy by closing the deployment loop, owning customer relationships, driving and prioritizing the roadmap, defining KPIs for physical AI deployments, and accelerating iteration between field data and engineering.
Company Description
Role Description
What You’ll Do
Qualifications
Bonus Points
Why Join Us
Autonomique is at the forefront of innovation in Physical AI, addressing key challenges in autonomy such as perception, reasoning, and dexterity. Our robotics intelligence framework delivers reliable, autonomous solutions for industries with complex operational demands. With advanced bi-manual robots, we are enabling groundbreaking advancements in manufacturing by empowering robots to perform critical real-world tasks. We are driven by the mission to make autonomous systems practical and impactful today.
This is a high-impact, high-ownership role for a builder who wants to shape our product roadmap alongside the leadership team. You will work directly with the founding team — sitting at the intersection of live deployments, customer operations, and engineering — to define what our robots should do next and why. We are looking for someone who values significant equity participation and wants to capture the upside of the value they create. You won't just be an employee; you will be a key architect of our success.
- Close the Deployment Loop: Systematically capture learnings from live robot deployments — failure modes, operator friction, edge cases — and translate them into clear, prioritized product requirements for the engineering team.
- Own the Customer Relationship: Engage directly with customers to surface unspoken needs, map operational workflows, and ensure our product roadmap reflects what matters most in the field.
- Drive the Roadmap: Define, prioritize, and communicate a product roadmap that balances short-term customer needs with long-term platform capabilities — and maintain alignment across engineering, operations, and leadership.
- Define Success Metrics: Establish and track the KPIs that matter in physical AI deployments — task success rate, intervention rate, cycle time, uptime — and use them to drive continuous improvement.
- Accelerate Iteration: Build tight feedback loops between field data, customer conversations, and development cycles so the team ships improvements faster and with greater confidence.
- Experience: 5+ years in product management for complex technical products — robotics, industrial automation, deep tech, or operational software.
- Deployment Track Record: Proven experience taking products from pilot to production in high-stakes operational environments where failures have real business consequences.
- Customer Fluency: Comfortable engaging with industrial operators and enterprise stakeholders, extracting unspoken needs, and turning them into actionable product decisions.
- Technical Credibility: Understands robotic systems well enough to engage meaningfully with engineers — familiar with autonomy stack concepts, sensor systems, and software pipelines. No need to code, but never lost in a technical discussion.
- Cross-Functional Leadership: Strong communicator who can align engineers, operations, and leadership around a shared vision without direct authority.
- Experience in Tier-1 automotive, biopharma, logistics automation, or other precision-critical industrial environments.
- Familiarity with robotic fleet management, telemetry, and operational KPI frameworks.
- Ownership: We offer a substantial equity package designed for those who believe in our mission and want to be rewarded for the company's long-term success.
- Impact: Work directly on real-world projects and see your code deployed in the real world immediately. We are already shipping robots in production.
- Culture: A collaborative, high-velocity supportive environment conducive to both personal and professional growth.
Similar Jobs
Artificial Intelligence • Robotics • Automation • Manufacturing
Own product direction for robotics and autonomy: capture deployment learnings, engage customers, prioritize roadmap, define KPIs (task success, intervention rate, uptime), and accelerate iteration between field data and engineering to scale pilots into production.
Top Skills:
Autonomy StackOperational Kpi FrameworksPerceptionRobotic Fleet ManagementSensor SystemsTelemetry
3 Hours Ago
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Implement and deploy deep-learning, computer vision, and procedural modeling algorithms (primarily in Python). Apply state-of-the-art ML and graphics research to convert large 2D/3D geospatial datasets into high-fidelity 3D content. Collaborate with founders on product vision, manage code with Git, and deploy/test at scale using Unix-based systems.
Top Skills:
C++GitPythonUnix Shell
3 Hours Ago
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Implement deep-learning, computer vision, and inverse-procedural modeling algorithms in Python to convert large 2D/3D and geospatial datasets into high-fidelity 3D content. Apply cutting-edge ML/graphics research, collaborate with founders to define technical milestones, deploy and test code on remote Unix systems, and manage code with Git.
Top Skills:
C++GitPythonUnix Shell
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

.png)