Head of Practice Management & AI Data Centers, Infrastructure & Cloud

Magna AI; Riyadh; On-site; SAR 300,000 - 400,000; Full time

Job summary

A leading AI tech firm in Riyadh is seeking an experienced professional to own and scale their AI Data Center and Cloud Practice. This role demands comprehensive accountability for developing, deploying, and optimizing AI infrastructure while managing commercial aspects like revenue and P&L. Ideal candidates will possess over 15 years in data centers and cloud technologies with strong leadership in AI environments. Competitive compensation offered with opportunities to lead transformative AI initiatives.

Qualifications

• 15+ years in data centers, infrastructure, and cloud with AI/HPC exposure.
• Leadership in AI or hyperscale environments.
• Experience in design, build, and operation.
• Strong commercial ownership & executive presence.
• Deep understanding of AI workload physical implications.

Responsibilities

• Own, build, and scale the AI Data Center and Cloud Practice.
• Accountable for end-to-end ownership including deployment and operations.
• Govern product design, build, operation, and monetization.
• Manage commercial ownership for revenue and P&L.
• Ensure delivery governance and quality compliance.

Skills

Data center management

Cloud architecture

Financial modeling (CAPEX/OPEX)

Leadership in AI environments

Infrastructure engineering

Job description

Magna AI is a global integrated-value-chain AI transformation factory, architecting the future of the intelligent enterprise. Through a unified approach that spans strategy, engineering, integration, and operations, Magna AI delivers secure AI infrastructure, applications, and services designed to drive measurable, scalable, and organization-wide transformation. Powered by next-generation technology from Trend Micro, NVIDIA, and Wistron Digital Technology Holding Company, Magna AI enables enterprises to evolve into intelligent, adaptive, and future‑ready organizations confidently.

Building the enterprise AI economy.

Job Summary

Own, build, and scale the AI Data Center, AI Factory, Infrastructure, and Cloud Practice as a full-lifecycle, revenue-generating business unit. Accountable for end-to-end ownership across business case creation, design, build, deployment, and operations of AI-optimized physical and cloud infrastructure, including sovereign AI factories, enterprise AI data centers, and hybrid cloud platforms.

This role governs what we sell, how we design it, how we build it, how we operate it, and how we monetize it.

AI Data Centers & AI Factories (Physical Layer)

Full Lifecycle Ownership

• Business Case & Feasibility: CAPEX/OPEX, ROI, IRR, payback • AI workload demand modeling (training vs inference, burst vs steady) • Power, land, water, cooling feasibility • Sovereignty, residency, regulatory assessments • Phased scale strategy (pilot → scale → hyperscale)
• Scoping, Survey & Site Analysis: Site selection & due diligence • Grid & power interconnection • Environmental, thermal, seismic analysis • Network proximity & latency • Rack density & power planning
• Design & Engineering (MEP): High-density power (30–120kW+ per rack) • Liquid/immersion/hybrid cooling • Redundancy (N+1, 2N, distributed resilience) • Electrical systems (substations, UPS, generators) • CDU, chilled water, direct-to-chip • Fire, safety, physical security • Modular/containerized AI factories
• Operations & Lifecycle: AI DC operating models • Capacity expansion • Predictive/preventive maintenance • Energy efficiency & PUE • SLA governance • AI hardware refresh cycles

B. Infrastructure Stack (Inside the AI Data Center)

End-to-End Ownership

• Storage: High-throughput AI storage • Object/block/file • Tiered training pipelines • Data locality optimization

Practice Management Responsibilities

• Practice Architecture & Offerings: AI Factory advisory • Design & build • Infrastructure deployment • Hybrid cloud enablement • Managed operations • Reference architectures & repeatable assets
• Commercial & P&L Ownership: Revenue, margin, utilization • Pricing for AI factories, infrastructure builds, cloud & managed services • Large-scale AI deal shaping
• Delivery Governance: Lifecycle governance • Quality, risk, compliance • Executive escalation for mission-critical programs
• Talent & Capability Building: AI DC design • Infrastructure engineering • Cloud architecture • Operations • Competency models & certifications

Required Profile

• 15+ years in data centers, infrastructure, and cloud with AI/HPC exposure
• Leadership in AI or hyperscale environments
• Design, build, and operate experience
• Strong commercial ownership & executive presence
• Deep understanding of AI workload physical implications