Senior SRE & Automation Architect — GPU Cloud, Remote

Bitdeer Technologies Group; San Jose (CA); Remote; USD 180,000 - 260,000; Full time

Job summary

Bitdeer Technologies Group in the United States is hiring a Senior SRE to own the reliability of the customer-facing GPU cloud service end-to-end, from onboarding to post-incident recovery. You will design observability, automation, and operational practices for a 10,000-GPU cloud, ensuring high availability and dependable tenant experience.

You will operate production Kubernetes clusters, NVIDIA GPU operator, device plugin, MIG, and multi-tenant isolation; build self-service observability,

Qualifications

• 5+ years in SRE / cloud operations, with at least 2 years operating GPU workloads at scale.
• Deep understanding of Kubernetes operations and GPU workload management (NVIDIA GPU operator, device plugin, MIG, time-slicing, GPU scheduling).
• Experience with topology-aware scheduling and GPU-specific resource management.
• Hands-on experience building multi-tenant cloud platforms with strong isolation guarantees.
• Customer-facing cloud service experience — defining and operating against customer SLAs/SLOs, handling tenant incidents and communications.
• Experience with bare-metal server provisioning and lifecycle automation (Ironic, MAAS, or custom).
• Proficiency in Terraform, Helm, and GitOps workflows (ArgoCD/Flux).
• Strong SRE background: SLI/SLO/SLA frameworks, error budgets, incident management, capacity planning.
• Experience with Prometheus, Grafana, and alerting at scale.
• Strong programming skills in Go or Python for automation / operator development.
• AIOps aptitude — you view the control plane as an execution surface for automated remediation, not just a scheduler.
• Runbook-as-code mindset — every SRE playbook you write should be executable by the platform.

Responsibilities

• End-to-end reliability of the customer-facing GPU cloud service — availability, job completion, provisioning latency, and tenant experience.
• Production Kubernetes clusters optimized for GPU workloads at scale (100–10,000 GPUs) as the runtime substrate for customer workloads.
• Nvidia GPU operator, device plugin, MIG configuration, GPU time-slicing, and multi-tenant GPU allocation policies.
• Topology-aware scheduling: GPU locality, NVLink domain awareness, network rail affinity — placing customer jobs on the right hardware.
• Customer & tenant lifecycle: onboarding, quota management, isolation enforcement (namespaces, network policies, RBAC, resource quotas, pod security), and offboarding/reclamation.
• BMaaS: automated provisioning, tenant handoff, lifecycle, and reclamation.
• SLIs/SLOs/SLAs for the customer cloud service: cluster availability, job completion rates, provisioning latency, API availability.
• Incident management with customer communication: runbook automation, escalation, customer-facing status updates, and post-incident reviews.
• Monitoring & observability stack: Prometheus, Grafana, Alertmanager, PagerDuty — tenant-aware dashboards and alerting.
• GPU node failure handling: automated detection, drain/cordon/taint, and workload rescheduling — minimizing customer-visible impact.
• Infrastructure-as-code: Terraform providers/modules, Helm, and GitOps (ArgoCD/Flux) across GPU clusters.
• Customer-facing operational readiness: service documentation, tenant runbooks, capacity planning, and support tiering.

Skills

SRE / cloud operations

Kubernetes operations

GPU workloads at scale

Multi-tenant cloud platforms

Incident management

Terraform

Helm

GitOps (ArgoCD/Flux)

Prometheus & Grafana

Go or Python

Runbook automation

Tools

NVIDIA GPU operator

Ironic/MAAS

ArgoCD/Flux

Prometheus

Grafana

Job description

Bitdeer Technologies Group in the United States is hiring a Senior SRE to own the reliability of the customer-facing GPU cloud service end-to-end, from onboarding to post-incident recovery. You will design observability, automation, and operational practices for a 10,000-GPU cloud, ensuring high availability and dependable tenant experience.

You will operate production Kubernetes clusters, NVIDIA GPU operator, device plugin, MIG, and multi-tenant isolation; build self-service observability,