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Software Engineer, AI Productivity

Physical Intelligence· Software Engineering
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San FranciscoFull-timePosted 1mo ago

About the role

Software Engineer focused on AI productivity to build and roll out internal tools and workflows that enable the company to use AI effectively across teams.

Responsibilities

  • Own AI tooling adoption across π: Identify where AI tools can improve velocity, build or integrate the right solutions, teach teams how to use them, and drive adoption.
  • Build internal AI tooling and integrations: Build backend services, scripts, workflows, user interfaces, LLM integrations, and agent infrastructure.
  • Make AI agents ergonomic: Own workflows for cloud agents, agent management, and internal automation that are easy to use, easy to monitor, and easy to trust.
  • Build tools for engineering, research, and operational velocity: Help engineers use AI to write, test, debug, review, and validate code faster. Empower researchers to extract signals and iterate quickly and confidently. Work with operations and recruiting to understand their workflows and build tools that give them leverage.
  • Own best practices and enablement: Create playbooks, examples, onboarding, office hours, demos, and shared workflows that help people learn from the best AI users at π.
  • Partner on security and data access: Ensure AI tools have the right access to be useful while respecting data boundaries, permissions, and company policies.
  • Evaluate build vs. buy: Maintain a strong perspective on the AI tooling ecosystem, evaluate commercial tools, and recommend what π should adopt.
  • Measure impact: Define success metrics for adoption, productivity, and satisfaction. Use feedback and data to understand what is working, what is not, and where to invest.

Qualifications

  • Strong software engineering fundamentals and the ability to ship quickly.
  • Deep excitement about AI tools and strong opinions about how they should be used.
  • Hands-on fluency with AI coding workflows and modern LLM-based tools.
  • Technical flexibility: ability to build backend services, internal tools, integrations, automation, and user interfaces.
  • Strong product judgment and taste for developer experience and internal tooling.
  • High empathy and excitement to work across engineering, research, operations, recruiting, and other teams.
  • Ability to learn unfamiliar systems quickly and operate across many technical domains.
  • Good judgment around security, permissions, data access, and safe tool rollout.
  • Clear communication, documentation, and teaching ability.
  • Comfort driving adoption, not just writing code.

Skills

Required:Software engineering fundamentalsAI tooling and workflowsFrontend and backend toolingSecurity and data accessCross-functional collaboration
Last updated Sep 16, 2026. Interested? Apply on the company site.
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About Physical Intelligence

Physical Intelligence (π)

Physical Intelligence is bringing general-purpose AI into the physical world.

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