AI Compute Reliability Engineer — Scale & Incident Leadership

Fluidstack; Seattle (WA); On-site; USD 173,000 - 224,000; Full time

Job summary

Fluidstack is building civilization-scale infrastructure for AI. The Data Center Operations Team focuses on running reliable, scalable compute for leading customers, owning SLAs, and coordinating incident response as sites come online and scale from tens to hundreds of gigawatts.

If you have experience supporting large-scale HPC, cloud, or AI lab workloads, can debug distributed systems across layers, and communicate incident updates clearly to customers, you may fit this role.

Qualifications

• Experience supporting large-scale compute customers (HPC, cloud, or AI labs) at a technical level.
• Ability to debug distributed systems across layers.
• Experience writing incident updates trusted by customers.
• Proactive in driving fixes with production teams.
• Bonus: GPU training workloads; InfiniBand or RoCE; Slurm or Kubernetes; NCCL debugging.

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.

Skills

Large-scale compute

Distributed systems debugging

Incident communication

Customer workload reliability

GPU training workloads

Job description

Fluidstack is building civilization-scale infrastructure for AI. The Data Center Operations Team focuses on running reliable, scalable compute for leading customers, owning SLAs, and coordinating incident response as sites come online and scale from tens to hundreds of gigawatts.

If you have experience supporting large-scale HPC, cloud, or AI lab workloads, can debug distributed systems across layers, and communicate incident updates clearly to customers, you may fit this role.