AI Hiring Index

1X · Infrastructure · Unspecified · Posted 2026-07-30

Software Engineer - NEO Reliability

1X · San Carlos, CA · $200k–300k base

This range's midpoint is above 70% of posted infrastructure ranges at AI companies right now. See the salary index.

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ABOUT 1X

We're building humanoid robots that work in the home, doing the chores, handling the tasks, and giving people their time back. Simple, but it's not. To do this right we have to solve robotics, AI, and manufacturing at the same time, at scale, in a form factor safe enough to live with your family. If you're inspired by this, you'll thrive here. We've been at this since 2014, and we're at the point where the hard problems are behind us and the hard work is in front of us.

NEO is our flagship, a home robot designed to move, learn, and operate in the real world alongside real people. We're not demoing it, we're shipping it.

If you've spent your career on problems that matter and want to see them reach the world, this is that moment. We're scaling, hiring with intention, and we need people who want to build something that genuinely changes how humans spend their time, safely creating abundance for all.

ABOUT THE TEAM

Our team owns the reliability and testing plan for every software system that runs on the robot or talks to it. That covers the front end, back end, cloud, mobile, on-robot services, and the embedded stack. Our work runs from hardware-in-the-loop testing and e2e regression through incident management, on-call, observability, release gating, and the SLOs that tell us what reliable actually means. From the first test a developer writes to the moment the robot moves in someone's home, we make robot software something the company can trust at fleet scale.

YOUR CHARTER

Own software reliability as a product. Start from the whole system and drive reliability practices as far down the stack as they need to go, from web and cloud through mobile, on-robot services, and embedded. You will build and own parts of an integrated testing package that checks the system e2e, starting with a developer test and ending with real robot movement. This is critical path work. As we scale from hundreds to tens of thousands of robots, whether customers can trust their robots, and whether our engineers can move fast, comes down to this layer.

KEY OUTCOMES

- Deliver an integrated testing package that covers every layer of the stack, from web and cloud to mobile, on-robot services, and embedded, and push those reliability standards steadily deeper over time.

- Own e2e testing that starts with a developer test and ends with robot movement, and put real numbers on that movement, those actions, and the robot's health.

- Triage reliability issues, find where the edges of a problem are, and route them to the right software or hardware team.

- Set the pace for software reliability best practices across the org, for internal teams and external customers.

KEY COMPETENCIES

- You work across the full stack, from infrastructure and systems out to the embedded edge, and you switch languages and technologies quickly as the work demands. You do not have to be an expert at every layer, but you carry sound reliability thinking into any of them.

- You understand how a mechatronics stack comes together, so you can find the edges of a problem and tell whether it sits in software or hardware. You treat sensing, telemetry, and logging as first class parts of reliability.

- You treat reliability as a product with real users, and you own your work e2e and ship without waiting to be told.

- You communicate clearly with internal and external stakeholders, turn data into findings people can act on, present them to stakeholder groups, and raise the bar for the people around you.

MINIMUM REQUIREMENTS

- Strong software engineering background with real depth in at least one layer of the stack (cloud and backend, systems, or embedded) and the range to reason across the rest.

- Experience building test and reliability infrastructure, or distributed systems at scale, such as APIs, real time data pipelines, monitoring, and incident management.

- Strong DevOps and Linux skills, including CI/CD and infrastructure as code, and fluency in Python …

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