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CrusoeCrusoeSan Francisco, CA

Senior Staff Cloud Support Engineer

Leads escalations for complex cloud incidents in AI infrastructure, designs reliability improvements for Kubernetes and GPU clusters, troubleshoots AI/ML workloads, and mentors engineers. Requires 8+ years in SRE/DevOps/HPC with deep Linux, networking, and customer expertise.

180k – 220k/yr
On-site8+ YOESupport Engineering

About the role

Technical Leadership & Escalations

  • Serve as highest-level escalation point for complex P1/P0 incidents.
  • Lead cross-functional root cause investigations involving compute, networking (IB/RDMA/RoCE), storage, and orchestration layers.
  • Partner with SRE, Software teams (Storage, Networking, Compute, K8) to design systemic fixes rather than recurring workarounds.

Reliability Architecture

  • Design and improve node validation, burn-in processes, performance baselining, and release readiness.
  • Influence Kubernetes architecture, workload orchestration (Slurm, Terraform), and AI/ML cluster stability.
  • Reduce MTTR and incident recurrence through structural improvements.

AI/ML Infrastructure Expertise

  • Troubleshoot NCCL, IB, GPU driver/firmware issues, distributed training failures.
  • Support complex AI workloads (training + inference) with performance tuning and observability improvements.

Customer-Facing Authority

  • Act as senior technical advisor during high-risk customer incidents.
  • Deliver executive-ready RCAs with clarity and confidence.
  • Drive trust through transparency and technical depth.

Mentorship & Standards

  • Mentor P3/P4 engineers.
  • Define SOPs and technical standards for support excellence.
  • Partner with Enablement to raise the technical bar across the organization.

What You Bring to the Team

  • 8+ years experience in SRE, DevOps, HPC, or Cloud Infrastructure roles.
  • Advanced Linux systems expertise.
  • Deep Kubernetes operational experience (CKA-level or higher).
  • Strong networking knowledge: Infiniband, RDMA, RoCE, SDN.
  • Experience supporting AI/ML workloads at scale (GPU clusters).
  • Proven track record of resolving multi-layer, distributed system failures.
  • Strong customer communication and executive-facing presence.

Benefits

  • Competitive compensation
  • Restricted Stock Units
  • Paid time off & paid holidays
  • Comprehensive health, dental & vision insurance
  • Employer contributions to HSA account
  • Paid parental leave
  • Paid life insurance, short-term and long-term disability
  • Professional development & tuition reimbursement
  • Mental health & wellness support
  • Commuter benefits (parking & transit)
  • Cell phone stipend
  • 401(k) Retirement plan with company match up to 4% of salary

Compensation Range: up to $180,000 - $220,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.

Skills

LinuxKubernetesInfiniBandRdmaRoceSdnNcclGPUSlurmTerraform
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