Senior SRE and Automation Engineer Customer Facing

You will own the reliability of customer-facing GPU cloud services. You will operate Kubernetes GPU clusters, manage tenant lifecycle and bare-metal provisioning, define service objectives, automate remediation, maintain observability, and communicate during customer incidents.

Responsibilities

• Operate customer-facing GPU cloud services and production Kubernetes clusters
• Manage Nvidia GPU Operator, device plugins, MIG, GPU time-slicing, and allocation policies
• Implement topology-aware GPU scheduling
• Manage tenant onboarding, quotas, isolation, offboarding, and reclamation
• Automate bare-metal provisioning and tenant lifecycle management
• Define and operate SLIs, SLOs, and SLAs
• Manage incidents, customer communications, and post-incident reviews
• Build tenant-aware monitoring, dashboards, and alerting
• Automate GPU node failure detection, workload draining, and rescheduling
• Manage infrastructure as code with Terraform, Helm, and GitOps
• Maintain service documentation, tenant runbooks, capacity plans, and support tiering
• Build self-service customer observability

Requirements

• 5+ years of SRE or cloud operations experience
• At least 2 years operating GPU workloads at scale
• Kubernetes operations and GPU workload management expertise
• Experience with Nvidia GPU Operator, device plugins, MIG, time-slicing, and GPU scheduling
• Experience with topology-aware scheduling and GPU resource management
• Experience building multi-tenant cloud platforms with isolation guarantees
• Customer-facing cloud service and SLA or SLO experience
• Bare-metal provisioning and lifecycle automation experience
• Terraform, Helm, and GitOps proficiency
• Knowledge of SLI, SLO, SLA, error budgets, incident management, and capacity planning
• Experience with Prometheus, Grafana, and alerting
• Go or Python programming skills
• AIOps and runbook-as-code experience