About the role
About Applied Intuition 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 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. Dana is Applied's agentic platform for physical AI industries: apps, agents, and data on one governed platform. You will own Dana's agent platform: how agents are built, run, evaluated, governed, and improved. You embed with the agent engineering team and own the product in detail, from harnesses and sandboxing to evals, model serving, and memory. We weight depth of agent experience over years; former founders are welcome. At Applied Intuition, you will: Own the agent platform product end to end, from how agents are created to how they're trusted in production Work with engineers daily on what is built and how it's built, and own the product and technical tradeoffs Make build/buy/partner calls across the agent stack (harnesses, sandboxing, evals, serving) and defend them with evidence Prototype and build on the platform yourself Track the agent landscape (labs, infra startups, open source) and keep our stack choices ahead of it We're looking for someone who has: Bachelor's Degree or higher in a relevant field Hands-on experience with agents: shipped an agent product, built harnesses or eval loops, or founded in the space Fluency in the current agent stack: tool use and MCP, sandboxing, evals, serving, context and memory Deep, current knowledge of the agent landscape and where it's going Technical competence to make tradeoffs with engineers and prototype within the platform using AI tools A record of shipping fast