About the Role:

The Manager – AI Solutions Onboarding is a customer-facing role responsible for implementing, configuring, and supporting the onboarding of enterprise and government clients onto Ooredoo’s GPU-as-a-Service platform. The role ensures seamless activation of GPU environments by handling system configuration, integration with customer workloads, and providing post-onboarding technical assistance.

This role requires hands-on experience with GPU infrastructure, container orchestration, cloud and hybrid deployment models, and customer training/support, working closely with solution architects, delivery teams, and account managers to ensure a smooth onboarding experience and early customer success.

Functional Context:

This role sits within the Professional services team and directly contributes to project acquisition and delivery. The Manager leads the technical realization of AI solutions, ensuring architectural consistency, operational scalability, and compliance with local regulatory standards. The role collaborates closely with presales, delivery, and vendor teams to ensure successful execution of complex AI and infrastructure projects.

The Professional Services department is a key pillar in the newly created Business solution division focused on providing solutions to Customers across Networks, Security and Hybrid cloud including the AI Solutions and GPUs. The professional services team is the overall lead in acquisition and delivery of projects.

Key Responsibilities:

• Act as the technical lead for onboarding new enterprise and government clients to the Ooredoo GPUaaS platform.
• Understand the customer requirements for proper onboarding of the AI Solution.
• Deploy, configure, and validate GPU workloads for customer environments (cloud, hybrid, or on-prem).
• Integrate customer AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face) with Ooredoo GPU infrastructure.
• Set up and troubleshoot NVIDIA-powered environments (DGX, L40S, A100) and ensure optimal performance.
• Configure container environments (e.g., Docker, Kubernetes) for running AI/ML workloads on GPU nodes.
• Coordinate with storage and networking teams to Configure Storage and networking as per the requirements
• Validate System performance benchmarks during onboarding.
• Ensure proper integration with orchestration tools like Kubeflow, MLflow, or Slurm if used by the customer.
• Conduct validation testing, PoC trials, and GPU workload benchmarking to meet SLAs and customer expectations.
• Implement and verify security controls including user access, RBAC, data encryption, and network isolation.
• Provide technical training and documentation to customer teams on managing and optimizing their GPU environments.
• Capture and escalate technical issues to delivery and support teams as needed, ensuring resolution and transparency.
• Assist with system health checks, monitoring setup, and usage reporting during onboarding.
• Collaborate with architects and sales teams to ensure each onboarding is aligned with the designed solution.
• Maintain customer onboarding checklists, deployment documentation, and handover reports.

Minimum Entry Qualifications:

Bachelor’s degree in Computer Science, IT Infrastructure, or related field

Minimum Experience, Essential Knowledge & Skills:

• Minimum 10 years’ work experience
• 7+ years in infrastructure deployment, DevOps, or technical onboarding roles.
• Hands-on experience with GPU compute environments (NVIDIA DGX, cloud GPU VMs, etc.).
• Familiarity with containerization (Docker/Kubernetes) and AI/ML frameworks.
• Strong understanding of networking, storage, and cloud services as related to AI workloads.
• Customer support and troubleshooting experience in technical delivery settings.
• Ability to communicate technical concepts clearly to non-technical stakeholders.

Professional Experience:.

• Familiarity with Qatari and regional ICT compliance standards (e.g., CRA, Q-CERT).

Excellent Analytical and Problem-Solving Skills:

Ability to identify the customer requirements and convert them into a new potential AI use case or identify an existing use case, thereby helping Customer to build the AI solution

Strong Communication and Interpersonal Skills

• Ability to collaborate effectively with various Customers and internal stakeholders and communicate complex Solutions and AI use cases clearly