Customer Reliability Engineer

Fluidstack; New York (NY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Fluidstack is seeking a Production Engineer to own reliability for high-demand customer workloads and SLA management. You will debug across the full stack, from hardware to scheduler, ensuring live systems stay online during AI training runs.

You will draft precise incident updates, drive root-cause analyses, and push the engineering teams to fix underlying causes rather than symptoms. GPU workloads, InfiniBand, Slurm, and Kubernetes experience are a plus.

Qualifications

• Experience supporting large-scale compute customers (HPC, AI labs, cloud).
• Ability to debug distributed systems across multiple layers.
• Proven track record communicating incidents with technical depth and timely updates.
• Experience driving root-cause analysis and follow-up actions with engineering teams.
• Bonus: GPU training workloads, Slurm, NCCL, InfiniBand.

Responsibilities

• Own reliability for named customer workloads and SLAs.
• Debug across hardware to fabric to scheduler during training runs.
• Manage customer-facing incident updates with clear, technical communication.
• Turn recurring customer pain into engineering fixes with production teams.

Skills

Distributed systems debugging

Incident communication

Customer-focused support

HPC/AI compute experience

Tools

Kubernetes

Slurm

NCCL

InfiniBand

Job description

About Fluidstack

We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had 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. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

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.

We hire people who care deeply about this problem space. If that is you, please apply!

How We Operate

• Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role.




• Insane urgency. We drive everything forward as fast as possible.




• Reason from 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.




• Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world.

The Production Engineering 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.

Role Scope

• 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.

What We're Looking For

• 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.

We are committed to pay equity and transparency.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.