Staff Software Engineer

Staff Software Engineer

Tutor Intelligence is building the technology and processes to let robots go where they've never gone before: the average American factory. We understand that general-purpose and generally-intelligent robots are going to be built in our lifetimes, and we're combining human and artificial intelligence to lead the charge. As an AI software company who deploys its inventions directly into the facilities that need them, on state-of-the-art hardware, every line of code written at Tutor has a direct impact on the global, physical economy.

We are looking for a Staff Software Engineer to lead the design and implementation of core software systems across our stack. This role is less about writing isolated features and more about owning architecture, setting technical direction, and building scalable, reliable platforms that support machine learning, robotics, and operations at scale.

You will work across backend services, data and ML infrastructure, internal tools, and customer-facing systems, while collaborating closely with robotics, hardware, and operations teams. Robotics is part of the domain, but this role is primarily about building high-leverage software systems that make the entire company faster and more effective.

Requirements

• Strong programming ability and experience building large, production software systems.
• Proven track record of owning and evolving complex systems over time.
• Experience working across backend, infrastructure, and application layers.
• Comfort operating in ambiguous problem spaces and making pragmatic architectural tradeoffs.
• Clear communicator who can lead technical discussions and align teams.

Nice to haves (zero or more)

• Experience with Python, TypeScript, Go, or similar languages.
• Experience with ML platforms, data pipelines, or ML-adjacent infrastructure.
• Experience with cloud infrastructure, containers, CI/CD, and developer tooling.
• Familiarity with robotics or hardware-integrated systems (not required).
• Startup experience or experience building systems from zero to production.