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Physical Intelligence is building general-purpose AI for the physical world through foundation models and learning algorithms for robots and physically-actuated devices. This Software Engineer role focuses on AI productivity and sits within the Runtime team, which owns core systems for operations and research.
You will own AI tooling adoption across the company, identifying where AI can create leverage and building reliable internal tools and workflows. Key responsibilities include:
- Identify and implement AI tools to improve velocity across engineering, research, and operations teams
- Build backend services, scripts, workflows, user interfaces, LLM integrations, and agent infrastructure
- Make AI agents ergonomic by owning workflows for cloud agents, agent management, and internal automation that are easy to use, monitor, and trust
- Help engineers use AI to write, test, debug, review, and validate code faster
- Empower researchers to extract signals and iterate quickly
- Work with operations and recruiting to understand workflows and build tools that give them leverage
- Create playbooks, examples, onboarding, office hours, demos, and shared workflows to help teams learn from best AI users
- Partner on security and data access, ensuring AI tools have appropriate permissions while respecting data boundaries
- Evaluate build vs. buy decisions in the AI tooling ecosystem
- Define success metrics for adoption, productivity, and satisfaction; use feedback and data to guide investment
You will partner deeply with teams across Physical Intelligence to understand their workflows, build tools that fit how they work, and drive adoption until those tools become part of the operating rhythm.
Requirements:
- Strong software engineering fundamentals and 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
Bonus: Experience building developer tools, agents, or automation platforms; experience building internal tools for research, robotics, or operationally-intensive problems; familiarity with React, TypeScript, Python, Postgres, ClickHouse, GCP, and Kubernetes.
