Technical Program Manager
Applied Intuition
- Location
- Sunnyvale
- Employment
- Full Time
- Work model
- On-Site
- Level
- Mid
- Posted
- 174d ago
About this role
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co . We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions About the role Applied Intuition is building Dana, the agentic platform for Physical AI, bringing the power of agents on top of a decade of tooling, infra and data expertise to accelerate the development of autonomy across every domain. Applied Intuition is looking for a Technical Program Manager passionate about building the agentic tooling platform that powers Physical AI. Our TPMs own roadmap execution through sharp cross-functional planning, clarity, and proactive risk management, acting with thoughtful urgency to drive decisions and outcomes. We partner with every function to deliver real-world deployments across domains (Cars, Trucks, Mining, and more), levels of autonomy (L2++ to L4), and geographies. This position will work cross-functionally with our Engineering, Design, Customer & Product teams. At Applied Intuition, you will: Partner with Simulation teams to define and shape the long-term vision and strategy for Applied's Autonomy Tooling platforms Drive the execution of programs that integrate simulation deeply into the ML development loop, establishing a seamless, reliable path for model training, offline evaluation, and validation Lead complex, cross-functional programs to platformatize and scale critical simulation workflows for both internal and external customers, accelerating developer velocity Own programs spanning multiple organizations, tracking progress and ensuring successful delivery of milestones, metrics, and final deliverables Continuously engage customers to surface pain points, translate their workflows into product gaps, and inform future engagements Navigate ambiguity and manage critical upstream/downstream dependencies across organizational boundaries, serving as a trusted technical partner to Engineering and Product We're looking for someone who has: Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent hands-on experience 3+ years steering technical programs within a software engineering or large-scale infrastructure environment Background leading projects that touch autonomous system development, simulation techniques and data pipelines A history of taking complex technical programs from start to finish, keeping timelines, risks, and dependencies aligned across many stakeholders Sharp communication and interpersonal instincts, able to translate complex technical ideas for both research and infrastructure audiences Nice to have: A solid technical foundation, ideally with hands-on software development under your belt Prior work in Physical AI: Simulation: Exposure to autonomous system simulation, log playback