About the Role
The Consultant – Operations Oversight & Performance, AI Infrastructure is responsible for overseeing the ongoing operational delivery of GPU infrastructure AI Runtime Layer after go-live. This role ensures that Kubernetes, GPU scheduling, container runtime, workloads, and autoscaling are operated to agreed performance standards while driving continuous improvement through structured oversight.
Ready to apply for roles like this?
Unlock the company name and direct application link. Subscribers get instant access to fresh jobs across Dubai, Abu Dhabi and Riyadh, many with visa support.
Unlock employer & apply directly
Responsibilities
- Define, agree, and monitor operational KPIs and SLAs with third parties (availability, incident response, resolution times, change success rate, capacity utilization, etc.).
- Oversee the 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 the management of container runtime, AI workloads (training/inference), and autoscaling.
- Review and 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 third parties 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.
Qualifications
Required Experience & Background:
- 10 years in GPU and HPC infrastructure operations, service management, or managed-service oversight roles.
- 7+ years Kubernetes experience (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
