Customer Reliability Engineer

About Us

We exist to make humanity more free. Technology has historically given people more time for the things they want to do, instead of things they have to do. Powerful AI will be the biggest lever for human choice we've ever built—but only if models are aligned with what humanity actually wants. We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them—with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.

How We Operate

• Extreme ownership. Full autonomy. Own things end to end, often taking on scope outside your core role without being asked to get things done.
• Velocity. We drive everything forward as fast as possible.
• First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
• Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.

About the Data Center Operations Team

Examples of key problems the team is working on:

• Operate at the scale of a nation, not a building. The fleet you run will draw more power than some countries, on the way to 10s to 100s of GWs.
• Fly the plane while it's being built. Sites come online in pieces, and you keep the live ones running flawlessly while construction continues around them.
• Write the playbook, don't inherit it. No prior operations org has run at this speed and scale, so the standards you set become the standard.

Responsibilities

• Own reliability for named customer workloads: their clusters, their SLAs, their escalations.
• Debug across the full stack, hardware to fabric to scheduler, when a training run degrades.
• Run customer-facing incident communication with technical depth and no spin.
• Turn recurring customer pain into engineering fixes with the production teams.

Requirements

The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.

• You've supported large-scale compute customers (HPC, cloud, or AI labs) at a technical level.
• You debug distributed systems methodically across layers you don't own.
• You've written incident updates customers trusted more after reading.
• You push internal teams to fix causes, not symptoms, and follow up until they do.

Bonus: GPU training workloads. InfiniBand or RoCE. Slurm or Kubernetes. NCCL debugging.

Pay

Compensation Range: $173K - $224K