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Tutor Intelligence is building general-purpose, generally-intelligent robots deployed directly into real-world facilities. The company operates at the intersection of research and deployment, ensuring that real-world operation drives technology improvement and vice versa.
You will lead the platform and infrastructure team that enables AI agents to do engineering work at scale. This is a senior, organization-wide role with responsibility for the shared infrastructure that every team at Tutor depends on.
Key responsibilities include:
• Lead the team building infrastructure for AI agents: environments, tooling, observability, and context designed agent-first and for the humans directing them
• Own the "commons" serving the whole company: decide what the central team owns versus what stays with individual teams, arbitrate when teams need different things from shared systems, and document those decisions
• Be accountable for the shared layer: production, CI, security, compliance. Ensure problems reach the right hands within an hour and own the ones that are yours
• Work alongside the engineers who use your infrastructure: they operate what they use and expect you to be there with them when something breaks, fixing root causes not just symptoms
• Build and grow the team: hire senior engineers, scale the team only as fast as work requires, and set direction for how a small team plus AI agents cover a large surface area
You will be hands-on. The balance between what you build yourself and what you lead others to build depends on who you are and how the team grows.
Culture note: At Tutor, engineers don't file tickets and wait. When something breaks, they're on it immediately, often with an agent. The infrastructure team is expected to be there with them, not standing between them and the systems.
REQUIREMENTS:
• 10+ years in infrastructure, platform, or systems engineering, including several years leading a team or function
• Proven experience owning shared infrastructure that an entire engineering organization depended on
• Experience building for AI agents (not just with them): you have shaped environments, tooling, or workflows so agents could do real engineering work, and you have opinions about what that takes
• Accountability for production: on-call experience, incident response, postmortems, in environments where downtime had real cost
• Leadership style: you make others faster; your platform work was adopted because it helped, and users came to you first when it didn't
• Comfort with users who are also operators: you prefer engineers to fix their own problems in your systems rather than routing everything through you, and you build to enable that
• Strong written communication: the decisions and standards you write are read and followed
NICE TO HAVE:
• Robotics, hardware, or experience at a company where infrastructure includes machines in the field
• Experience as a first platform or first security lead at a growing company
• Experience building a small, senior team rather than a large one
Note: At Tutor, all R&D roles hold the title Member of Technical Staff (MoTS) with a level determined through the interview process. The company hires people, not slots, and expects flexibility as work evolves quarterly.
