Consultant – Operations Oversight & Performance, AI Infrastructure

Malomatia; Doha; On-site; QAR 180,000 - 300,000; Full time

Job summary

Malomatia is seeking a Senior Consultant for Operations Oversight & Performance of AI infrastructure to ensure GPU runtimes, Kubernetes clusters, and autoscaling meet agreed performance standards.

You will define KPIs, monitor GPU workloads, integrate observability with Prometheus/Grafana, and coordinate with stakeholders to drive continuous improvement while ensuring compliance and security across multi-cluster environments.

Qualifications

• 10 years in GPU and HPC infrastructure operations, service management, or managed-service oversight roles.
• 7+ years Kubernetes experience with GPU workloads at scale.
• Strong knowledge of CNCF ecosystem, operators, CRDs, and GPU-specific features (NVIDIA GPU Operator, DRA).

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.

Skills

GPU infrastructure

Kubernetes

Observability

Stakeholder management

Tools

NVIDIA GPU Operator

Prometheus

Grafana

Rafay

Kubernetes CRDs

Job description

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; elevate 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

• 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