Meta is seeking a senior infrastructure planning leader to join Data Center Central Planning. In this role, you will develop integrated, multi-year global data center capacity plans and scaling strategies that ensure Meta can deliver the right infrastructure at the right time, cost, and reliability, while staying adaptable under uncertainty. You'll translate fast-evolving demand signals-especially those driven by AI large clusters-into executable supply strategies and clear executive decision points. This is a high-leverage role operating at the intersection of data center planning, demand forecasting, infrastructure engineering, supply strategy. You will own our data center planning strategies and recommendations, drive cross-org alignment, and partner with stakeholders across capacity engineering, network, hardware, supply chain, finance, data science, and IDC delivery and operations teams to drive decisions through to implementation.
Responsibilities
Own multi-year DC capacity planning and the Plan of Record (PoR): Develop, maintain, and continuously refresh integrated global data center supply/capacity plans; drive monthly/quarterly updates to assumptions, constraints, and scenarios to ensure plans remain decision-grade and executable.
• Lead decision-quality tradeoffs for leadership: Apply quantitative and strategic judgment to build scenarios and evaluate alternatives; present clear options, tradeoffs, risks, and recommendations for multi-billion-dollar infrastructure investments and portfolio decisions.
• Drive AI large cluster planning outcomes: Partner with engineering and delivery stakeholders to incorporate AI-driven demand profiles, large-cluster requirements, and emerging constraints into the central plan; help shape the capacity and delivery strategy to support rapid AI evolution.
• Create durable planning frameworks (beyond "spreadsheet planning"): Improve the planning ecosystem by defining requirements for data quality, source-of-truth signals, and scalable planning workflows; partner with systems/tooling teams to uplevel automation and reliability of planning outputs.
• Identify constraints, dependencies, and mitigation strategies: Surface systemic risks (power, space, lead times, supply volatility, readiness, policy/legal, sustainability, etc.), define mitigation paths, and drive closure with accountable partners.
• Own executive communication and stakeholder alignment: Build the narrative and communications strategy for planning decisions (exec briefs, deep dives, recurring forums); drive alignment across diverse, high-seniority stakeholders with competing priorities.
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• BS in engineering, computer science, operations research, economics, or other quantitative/analytical field (or equivalent practical experience)
• 15+ years experience in infrastructure strategy, capacity planning, hardware/cloud infrastructure, supply strategy, or adjacent domains with demonstrated ownership of large, cross-org decisions
• Demonstrated strength in quantitative analysis and modeling (scenario analysis, sensitivity analysis, decision frameworks, optimizing under constraints/uncertainty)
• Strong understanding of large-scale infrastructure systems and how workload requirements map to data center constraints (power, space, networking, availability, lead times, etc.)
• Proven ability to operate autonomously in ambiguous environments and drive alignment to closure through influence
• Executive-level communication skills: able to synthesize complexity into decision-grade narratives for senior leadership
Preferred Qualifications
• Experience with AI infrastructure planning (training/inference demand patterns, large-cluster constraints, rapid shifts in demand and hardware assumptions)
• Experience owning or evolving planning systems / data pipelines / source-of-truth processes at scale
• Prior experience partnering with IDC delivery (construction, build programs, lease strategy, site/facility ops) and/or capacity engineering organizations
