Senior Software Engineer, AI-Augmented Development
Job Description
Job Description
The Company
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. Founded by a close-knit group of engineers out of MIT, Tutor Intelligence is an early-stage startup developing state of the art AI-powered robotics for American factories.
The Role
Something has changed. A year ago you wrote code by hand — and you were good at it. Then you started using Claude Code, Cursor, or similar tools and realized the game had fundamentally shifted. Now LLMs write the vast majority of your code, and you're producing more, better software than ever before. You didn't just try these tools — you went all in.
We're looking for a senior software engineer who has lived through this transition and come out the other side more productive, not less rigorous. Someone who understands that AI-augmented development isn't about generating slop — it's about a skilled engineer leveraging a force multiplier to ship things that used to take a team of five.
At Tutor, you'll build the distributed infrastructure, cloud services, user interfaces, and developer tooling that power intelligent robots in real factories. Your code ships to real robots that pick real things in real warehouses — not another SaaS dashboard. You'll work across the stack — backend services, frontends, CI/CD, ML pipelines, data systems — wherever the highest-leverage work is on any given day. Robotics experience is not required. Strong engineering judgment is. But if you've ever wanted to watch a robot do something because of code you wrote that morning, this is the job.
What You'll Do- Architect and build core software systems across backend services, cloud infrastructure, internal tools, and user-facing applications
- Ship fast by combining your own engineering expertise with LLM-based development workflows — and help the rest of the team do the same
- Own problems end-to-end: scope them, build them, deploy them, and keep them running in production
- Work directly with robotics engineers, ML engineers, and operations to understand what's needed and deliver it
- See your work come to life on physical robots — debug a deployment in the morning, watch it run on the factory floor in the afternoon
- Identify and eliminate bottlenecks in how the team builds, tests, and deploys software
- You were a strong software engineer before LLMs entered the picture. You have deep fundamentals — you understand systems design, debugging, performance, and how to write code that doesn't fall over in production.
- You've gone deep on AI-augmented development. Claude Code, Cursor, Copilot, aider — you've used one or more of these tools extensively and have strong opinions about how to use them well. You can articulate what works, what doesn't, and why a human in the loop still matters.
- You are pragmatic and fast. You'd rather ship something that works today than design the perfect abstraction for next quarter. You have good instincts for when to be careful and when to move.
- You are multidisciplinary. You don't hide behind a title. If the highest-value thing to do is write a React frontend, set up a Kubernetes cluster, or debug a data pipeline, you do it.
- You have 5+ years of professional software engineering experience, with meaningful work in Python.
- You are excited about working on-site with a small, intense team building physical products that operate in the real world. You think robots are cool — and you want to be the reason they get cooler.
All offers include generous equity, fully covered health + dental, and unlimited PTO.
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