---
title: 'Robotics Infrastructure Engineer at Tutor Intelligence'
canonical: 'https://feeny.ai/job/robotics-infrastructure-engineer-tutor-intelligence-watertown-q9cjbvy6j2db'
type: 'job'
last_seen: '2026-10-28'
---

# Robotics Infrastructure Engineer at Tutor Intelligence

- **Company:** Tutor Intelligence
- **Location:** Watertown, MA
- **Compensation:** $100k–$300k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-10
- **Last confirmed live:** 2026-10-28
- **Apply:** https://jobs.lever.co/tutorintelligence/fdb1c47e-4685-4ac7-b57f-f1ba1077c3ec

## Job description

## About Tutor

We believe robots are the biggest lever we have to making the physical world a better, more affordable place. But robots are a rounding error in our society: nearly nine out of ten American factories and warehouses don’t even have a single robot, and robots have yet to make their way into our homes or places of business. Tutor Intelligence is changing that. Tutor is a robotics research and deployment company, building generally capable robot hardware and artificial intelligence to enable robots to go where no robots have gone before. Sonny is a semi-humanoid robot with frontier dexterity approaching the human form. Cassie does back-breaking work, moving boxes, pallets, and bulk goods for businesses from family-owned manufacturers to some of the largest brands in the world. Tutor robots are manufactured at scale and operate as a network, combining the whole fleet’s learned experience to train ever more capable robot artificial intelligence. Founded at MIT and headquartered in Watertown, MA, our team is full stack: we design and manufacture robot hardware, train our own models, work directly with the smallest and largest end-customers, and maintain our fleet across the United States. We’re a team of researchers, engineers, technicians, operators, and sellers who love building things and solving hard problems. Our mission is grand: robots everywhere, for the common good, raising the standard of living across North America, and then the world.

## The Role

Robotics Infrastructure Engineer: Systems, Infrastructure & Reliability

We build robots that run 24/7 in production environments. We're looking for a hands-on engineer to own the reliability, infrastructure, and developer tooling that keeps our fleet running and our engineering team fast. You'll split your time between robot-side systems work, cloud infrastructure, and building automation that multiplies the team's output.

A significant portion of this role involves working with AI coding agents. You'll direct autonomous agents to diagnose CI failures, triage production issues, run automated security and compliance checks, and execute multi-step engineering tasks. Knowing how to scope work for an agent, review its output critically, and build tooling that agents can use effectively is as important as writing the code yourself.

## What You'll Do

- Own robot-side software (Python): Maintain the on-robot codebase that orchestrates arms, cameras, sensors, and I/O. Debug production hardware/software failures and ship fixes fast
- Build and maintain infrastructure as code: Manage cloud infrastructure — identity and access management, CI/CD credentials, secrets, container registries, cluster autoscaling — using declarative configuration and reproducible builds
- Drive build system and packaging migrations: Own the transition of robot software packaging to reproducible, hermetic build systems. Maintain machine images, dev environments, and deployment pipelines
- Build simulation and testing infrastructure: Develop end-to-end simulation systems that validate robot behavior without physical hardware — camera projection, kinematics, placement validation, fleet-wide calibration
- Develop and operate AI-powered engineering automation: Build autonomous agents that run nightly CI triage, security audits, infrastructure compliance checks, and code quality sweeps. Design the interfaces and instructions that make agents effective at real engineering work
- Improve observability and health monitoring: Instrument robot software with metrics and structured telemetry. Build alerting that catches problems before humans notice them
- Work across the stack: Touch frontend, backend, protobuf definitions, deployment tooling, and cloud services as needed. No part of the system is someone else's problem

## What We're Looking For

- 3+ years of Python in a systems context — not web/ML Python, but the kind where you deal with processes, hardware I/O, async, and real-time constraints
- Strong Linux systems knowledge: Memory management, device management, systemd, containers, networking, kernel tuning
- Infrastructure as code experience: Declarative infrastructure and configuration management tools. You've managed IAM, CI runners, secrets, and machine images programmatically
- Experience with real hardware: Robot arms, depth cameras, grippers, force/torque sensors, pneumatics, or similar
- CI/CD ownership: You've not just used CI — you've owned it. Runner infrastructure, flaky test triage, build caching, GPU-enabled pipelines
- Comfort with AI coding agents: You've used tools like Claude Code, Cursor, Copilot Workspace, or similar to do real engineering work — not just autocomplete, but directing agents through multi-step debugging, refactoring, and infrastructure tasks. You understand their failure modes and know when to trust vs. verify
- Strong debugging instincts: You can go from a vague production symptom to root cause across hardware, OS, network, and application layers
- Bias toward shipping over perfecting: You fix, monitor, iterate. Your commit history has more fix: than feat: and you're proud of that

## Nice to Have

- NixOS or reproducible build system experience
- Experience building or operating autonomous engineering agents/bots
- Robotics simulation (kinematics, camera models, physics)
- gRPC / Protocol Buffers
- Managed network infrastructure, VPNs, overlay networks
- Time-series databases and observability stacks

## About the Work Style

This is a high-autonomy, high-output role. On a typical day you might direct an AI agent to triage overnight CI failures while you debug a production robot issue, then spend the afternoon migrating a package to a new build system. You'll write a lot of code, but you'll also write a lot of prompts — and the best candidates will see those as the same skill.

Why Tutor? Whether you’re designing robots, closing deals, running deployments, or creating the processes that help us scale, your work doesn’t sit on a shelf. It shows up on real production floors, making physical work safer and more affordable. Our team of 160+ is driven by curiosity and a genuine love of building. Everyone here takes real ownership, learns fast, and holds a high bar while having each other’s backs. If you love hard problems and creating things that didn’t exist before, you’ll fit right in.

## Benefits

We take care of our team so they can do their best work. At Tutor, you’ll get: Fully employer-covered health insurance, so you’re protected without the premium. A managed 401(k) to help you plan for the future. Generous time off: unlimited PTO and all federal holidays off for full-time salaried employees, and 16+ days of accrued paid time off plus 1.5x pay on federal holidays for hourly employees. Regular in-office meals and team social events throughout the year. As Tutor grows, so will our benefits. We’re continuing to invest in ways to support our team at work and beyond. Tutor Intelligence is an equal opportunity employer and welcomes applicants from all backgrounds.

## About Tutor Intelligence

## Company Overview
- **One-liner**: Tutor Intelligence builds AI-powered robot workers for manufacturing and logistics, deploying intelligent physical automation that adapts to dynamic industrial environments.
- **Entity Type**: Private (Series A, total funding $78.7M)
- **Headquarters**: Watertown, Massachusetts, USA
- **Founded**: 2021 (earliest corporate round)
- **Founders**: Josh Gruenstein (CEO) and Alon Kosowsky-Sachs (Co-Founder)

## Core Business
- Primary industry/industries: Robotics, Artificial Intelligence, Industrial Automation, Logistics & Warehousing
- Target customers: B2B – manufacturing plants, warehouses, 3PLs, and large-scale industrial operations (Enterprise)
- Mission or purpose statement: "To build fundamental AI technology to enable generally capable robot workers and partner with industry to deploy them" – solving the hardest problems in physical machine intelligence.

## Products & Services
- **[Cassie](https://tutorintelligence.com/)**: A purpose-built robot for material handling – palletizing, depalletizing, and case picking. Deployed in days, handles unlimited SKUs, works 24/7 with a simple tablet interface. Pricing starts at $14/hour per robot or per-pick models.
- **[Sonny](https://tutorintelligence.com/)**: A humanoid robot designed for the "messy middle" of manual labor – complex assembly, irregular tasks. Industrial-grade hardware, trained on internet-scale data. Available for deployment starting late 2026.
- **Platform & Fleet Management**: Full B2B logistics workflow automation (replen to picking to palletizing) with per-pick pricing, remote 24/7 support, and continuous AI improvements.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding $78.7M (latest round: $40.5M venture round in June 2025; Series A $34M in December 2025 led by Union Square Ventures and Fundomo)
- **Notable Investors/Partners**: Union Square Ventures, Fundomo; partners with world’s largest 3PLs and brands (deployed in dozens of factories and warehouses)
- **Growth Signals**: Headcount grew 278.8% YoY to 69 employees (as of early 2026); 38 active job postings; monthly job postings up 40.7%; expanding into humanoid robotics with Sonny; offices across US, India, Canada, Portugal, South Africa.

## Competitive Advantages
- **Deployment speed**: Robots are operational "in days" without changes to existing infrastructure – reads pallet specs like human workers.
- **Flexible pricing**: Per-hour ($14/hr) or per-pick models with no contract lock-in, lowering cost of fulfillment by 20%+.
- **AI-first approach**: Robots learn from human interaction in real environments, continuously improving via an intelligence platform.
- **Proven real-world impact**: Already deployed across dozens of facilities for major brands, not just pilots.

## Strategic Focus
- Scale deployments of Cassie across more warehouses and factories.
- Launch Sonny humanoid robot in late 2026 for complex manual tasks.
- Continue advancing physical AI research (founded out of MIT CSAIL) to expand robot capabilities into new industries.
- Grow the fleet and per-pick pricing model to capture more of the B2B logistics workflow.

## Why Work Here
- **Culture**: Fast-paced startup with deep roots in MIT CSAIL research – a blend of cutting-edge AI/robotics and real-world industrial impact.
- **Work model**: On-site in Watertown, MA (employees work from physical offices). Offices also in India, Canada, Portugal, South Africa.
- **Growth**: 278% YoY headcount growth, 38 open roles across engineering, research, sales, and operations – strong upward mobility.
- **Roles**: Robotics engineers, perception engineers, full-stack developers, research scientists, field technicians, account executives, and more.
- **Perks**: Not explicitly listed, but emphasis on 24/7 remote support, always-on AI improvements, and no contract lock-in suggests a team that values reliability and customer success.
- **Engineering culture**: Focus on solving hardest problems in machine intelligence; teams work at the edge of AI, robotics, and operations.

## Sources
1. [tutorintelligence.com](https://tutorintelligence.com/)
2. [tutorintelligence.com/about](https://tutorintelligence.com/about)
3. [LinkedIn Company Page](https://www.linkedin.com/company/tutorintelligence)
4. [Built In Boston – Tutor Intelligence](https://www.builtinboston.com/company/tutor-intelligence)

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