Consultant – Operations Oversight & Performance, AI Infrastructure
Key Skills for This Role
Full Job Posting
Qualifications
- Required Experience & Background: 10 years in GPU and HPC infrastructure operations, service management, or managed-service oversight roles. 7+ years Kubernetes (CKA preferred); deep experience running GPU workloads at scale. Strong knowledge of CNCF ecosystem, operators, CRDs, and GPU-specific features (NVIDIA GPU Operator, DRA). Excellent understanding of GPU or high-performance compute operations, observability, and incident/change management. Strong analytical, reporting, and stakeholder management skills.
- Preferred Certifications: NCP-AII – NVIDIA-Certified Professional: AI Infrastructure NCP-AIO – NVIDIA-Certified Professional: AI Operations NCP-AIN – NVIDIA-Certified Professional: AI Networking Red Hat Certified Specialist in Containers and Kubernetes – OpenShift Container Platform 4.6 Red Hat Certified Specialist in OpenShift Administration Any service management or performance management credentials – advantageous Relevant Linux or systems certifications (RHCSA or equivalent) – advantageous
- 10 years in GPU and HPC infrastructure operations, service management, or managed-service oversight roles.
- Strong knowledge of CNCF ecosystem, operators, CRDs, and GPU-specific features (NVIDIA GPU Operator, DRA).
- Excellent understanding of GPU or high-performance compute operations, observability, and incident/change management.
- Strong analytical, reporting, and stakeholder management skills.
Responsibilities
- Define, agree, and monitor operational KPIs and SLAs with 3rd party (availability, incident response, resolution times, change success rate, capacity utilization, etc.). Escort Operation and hardening of Kubernetes clusters with GPU Operator, device plugins, DRA, MIG/time-slicing, and advanced schedulers (Kueue or equivalents). Review GPU-aware scheduling, fair-share/quotas, priority classes, preemption, and multi-tenancy isolation. Supervise manages container runtime, AI workloads (training/inference), and autoscaling. Review integrate observability (Prometheus/Grafana + DCGM), logging, and GitOps for the runtime layer. Support multi-cluster federation and cluster lifecycle (in partnership with Rafay layer). Conduct regular operational reviews of Advanced NOC performance, incident trends, problem management, and change records. Drive service improvement plans and hold 3rd party accountable for operational performance. Review capacity, lifecycle, and maintenance plans; escalate risks to the Program Delivery Lead. Ensure operational processes support future Platform foundation requirements (observability, identity, scheduling readiness). Coordinate planned works, maintenance windows, and operational communications with internal stakeholders. Maintain the operational risk register and support audit/compliance evidence collection.
- Define, agree, and monitor operational KPIs and SLAs with 3rd party (availability, incident response, resolution times, change success rate, capacity utilization, etc.).
- Escort Operation and hardening of Kubernetes clusters with GPU Operator, device plugins, DRA, MIG/time-slicing, and advanced schedulers (Kueue or equivalents).
- Review GPU-aware scheduling, fair-share/quotas, priority classes, preemption, and multi-tenancy isolation.
- Supervise manages container runtime, AI workloads (training/inference), and autoscaling.
- Review integrate observability (Prometheus/Grafana + DCGM), logging, and GitOps for the runtime layer.
- Support multi-cluster federation and cluster lifecycle (in partnership with Rafay layer).
- Conduct regular operational reviews of Advanced NOC performance, incident trends, problem management, and change records.
- Drive service improvement plans and hold 3rd party accountable for operational performance.
- Review capacity, lifecycle, and maintenance plans; escalate risks to the Program Delivery Lead.
- Ensure operational processes support future Platform foundation requirements (observability, identity, scheduling readiness).
- Coordinate planned works, maintenance windows, and operational communications with internal stakeholders.
- Maintain the operational risk register and support audit/compliance evidence collection.
Preferred Qualifications
- 7+ years Kubernetes (CKA preferred); deep experience running GPU workloads at scale.
- NCP-AII – NVIDIA-Certified Professional: AI Infrastructure
- NCP-AIO – NVIDIA-Certified Professional: AI Operations
- NCP-AIN – NVIDIA-Certified Professional: AI Networking
- Red Hat Certified Specialist in Containers and Kubernetes – OpenShift Container Platform 4.6
- Red Hat Certified Specialist in OpenShift Administration
- Any service management or performance management credentials – advantageous
- Relevant Linux or systems certifications (RHCSA or equivalent) – advantageous
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