FluidStack
Customer Reliability Engineer
San Francisco, CA$204k–$284kfulltimemidAdded today
About this role
Fluidstack seeks a Customer Reliability Engineer to own reliability for large-scale AI compute customers, debugging across the full hardware-to-software stack and driving root-cause fixes for infrastructure supporting frontier AI workloads.
What you'll do
- Own reliability for named customer clusters and SLAs, handling escalations end-to-end
- Debug distributed systems issues across hardware, fabric, and scheduler layers
- Communicate incident status to customers with technical accuracy and transparency
- Partner with production teams to convert recurring customer issues into engineering solutions
- Operate infrastructure at nation-scale power levels during concurrent site construction and deployment
What they're looking for
- Large-scale compute systems support (HPC, cloud, or AI labs)
- Distributed systems debugging across multiple layers
- Technical incident communication and customer-facing documentation
- GPU training workloads and optimization
- InfiniBand or RoCE networking
- Kubernetes or Slurm cluster management
- NCCL debugging and performance analysis
- Root cause analysis and systems troubleshooting
Opens the official application on the employer’s site. No login required.
FluidStack
FluidStack builds AI infrastructure at scale, developing data centers and warehouse operations designed to handle gigawatt-capacity compute deployment. The company is hiring for warehouse engineers, data center operations specialists, product engineers, and people leaders to support rapid infrastructure expansion across multiple sites.
- Website
- fluidstack.io
Likely interview questions
- Tell us about a time you debugged a complex issue across a stack you didn't fully own—how did you approach it?
- Describe an incident where you had to communicate with customers about a degraded system. How did you maintain trust?