Software Engineer, AI Productivity

Physical Intelligence; San Francisco (CA); Sur place; USD 140 000 - 230 000; Plein temps

Résumé du poste

Physical Intelligence is hiring a Software Engineer focused on AI productivity to build and roll out internal tools that accelerate AI use across the company. You will collaborate with engineering, research, operations, and people teams to understand workflows and create reliable tools that fit how they work.

You will build backend services, user interfaces, and integrations, drive adoption, and help scale AI solutions across PI with a focus on speed, reliability, and safe access to data.

Qualifications

• Strong software engineering fundamentals and the ability to ship quickly.
• Hands-on fluency with AI coding workflows and modern LLM-based tools.
• Experience building internal tooling and developer platforms.
• Good judgment around security, permissions, and data access.

Responsabilités

• Own AI tooling adoption across the company and drive user adoption.
• Build internal AI tooling, integrations, and agent infrastructure.
• Create ergonomic AI agents and workflows that are easy to use and monitor.
• Develop tools to increase engineering, research, and operational velocity.
• Share playbooks, onboarding, and demos to spread best practices.
• Collaborate with security and data teams to ensure proper access controls.

Connaissances

AI tooling

Backend services

LLM integrations

Developer experience

Security & data access

Outils

React

TypeScript

Python

Postgres

ClickHouse

GCP

Kubernetes

Description du poste

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.

As a Software Engineer focused on AI productivity, you will build and roll out the tools that help us use AI effectively across the company. You will work closely with engineering, research, operations, people, and other teams to understand how people work, identify where AI can create leverage, and turn those opportunities into reliable internal tools and workflows.

The Team

Runtime owns core systems that help π’s operations and research teams move quickly and reliably. This role will sit in Runtime and work alongside engineers focused on build systems, infrastructure, and developer productivity.

Your focus will be AI tooling: making AI agents, assistants, integrations, and automation useful across the company. You will partner deeply with teams across PI to understand their workflows, build tools that fit how they work, and drive adoption until those tools become part of the operating rhythm of the company.

In This Role You Will

• 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.

What We Hope You'll Bring

• 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.

Bonus Points

• Experience building developer tools, agents, or automation platforms.
• Experience building internal tools specifically for research, robotics, or operationally-intensive problems.
• Experience with our specific stack: React, TypeScript, Python, Postgres, ClickHouse, GCP, and Kubernetes.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.