Consultant – Operations Oversight & Performance, AI Infrastructure

Job Description

The Consultant – Operations Oversight & Performance, AI Infrastructure is responsible for Oversee OEM ongoing operational delivery after go-live. Ensure the GPU infrastructure AI Runtime Layer - Kubernetes, GPU scheduling, container runtime, workloads, and autoscaling are operated to agreed performance standards and drive continuous improvement through structured oversight.

Job Description

The Consultant – Operations Oversight & Performance, AI Infrastructure is responsible for Oversee OEM ongoing operational delivery after go-live. Ensure the GPU infrastructure AI Runtime Layer - Kubernetes, GPU scheduling, container runtime, workloads, and autoscaling are operated to agreed performance standards and drive continuous improvement through structured oversight.

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; escalat 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.

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

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