Software Engineer (AI Productivity)
Physical Intelligence
- San Francisco, United States
- Mid Level
- Posted
Skills
Required
- AI
- AI tools
- LLM-based tools
- software engineering
- writing code
Preferred
- workflows
- integrations
- data access
- backend services
- user interfaces
- automation
- make AI agents ergonomic
- scripts
Join π, a cutting-edge AI research and development company, as a Software Engineer focused on AI productivity. In this role, you will work alongside engineers dedicated to build systems, infrastructure, and developer productivity. Your primary focus will be on AI tooling, where you will identify opportunities for improvement, build and integrate solutions, and drive adoption across the company.
Experience with our specific stack: React, TypeScript, Python, Postgres, ClickHouse, GCP, and Kubernetes
Responsibilities
- You will also build internal AI tooling and integrations, make AI agents ergonomic, and create best practices and enablement resources.
- Additionally, you will partner on security and data access, evaluate build vs. buy options, and measure the impact of your work.
- Identifying areas where AI tools can improve productivity and driving adoption across the company.
- Building internal AI tooling and integrations, including backend services, scripts, workflows, user interfaces, and LLM integrations.
- Creating playbooks, examples, onboarding materials, and shared workflows to help teams learn from the best AI users.
- Good judgment around security, permissions, data access, and safe tool rollout
- Technical flexibility: ability to build backend services, internal tools, integrations, automation, and user interfaces
Requirements
- Strong product judgment and taste for developer experience and internal tooling
- Deep excitement about AI tools and strong opinions about how they should be used
Clear communication, documentation, and teaching ability
- Ability to learn unfamiliar systems quickly and operate across many technical domains
- Hands-on fluency with AI coding workflows and modern LLM-based tools
- High empathy and excitement to work across engineering, research, operations, recruiting, and other teams
- Strong software engineering fundamentals and the ability to ship quickly
- Comfort driving adoption, not just writing code
- Experience building internal tools specifically for research, robotics, or operationally-intensive problems
Preferred
- Experience building developer tools, agents, or automation platforms
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