Product Manager, Infrastructure Capacity Planning

MetaMenlo Park, CaliforniaOn-siteFull-timeSenior, 5–8 yearsListed 58 minutes ago

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About this role

Meta's Infrastructure organization provides the backbone on which the company operates — and today, this importance is significantly amplified by the vision of Super Intelligence. As a Product Manager on the Supply Planning And Capacity Ecosystems (SPACE) team, you will build products, tools, and policies that enable compute infrastructure to scale efficiently, supporting the massive demand powering our social media products and AI initiatives.

Capacity is a company investment priority and strategic differentiator. You will plan and optimize infrastructure resources, set capacity targets, and drive cross-functional teams — spanning engineering, data science, finance, supply chain, and data center construction — to meet those targets. You will also partner with product teams across Facebook, Instagram, WhatsApp, and monetization to align investment decisions with business outcomes during a period of rapid AI growth and new hardware adoption.

This role spans executive-level engagement and offers the opportunity to build lasting systems at scale. The team values collaboration, mentorship, and cross-functional problem-solving. If you're excited by navigating complex tradeoffs and shaping infrastructure strategy during transformative shifts, this role may be a strong fit.

Responsibilities

Proactively identify the important problems to solve (e.g. competitively, strategically, for customers, and in support of company goals)
Build a coherent strategy and roadmap for addressing these issues with measurable objectives
Facilitate the flow of information between everyone involved and create consensus around a vision, priorities and decisions
Drive, track, and document progress against roadmaps
Define a high standard of quality for product area and hold teams accountable to that bar
Make larger org and all of Product Management better by supporting Recruiting initiatives such as interviewing
Operate in varying degrees of ambiguity
Foster an environment where teams are able to advocate and pursue robust points of view while at the same time seeking consensus
Flexibility to adjust to top line company priority shifts
Scope: Independently identifies significant opportunities, brings subject-matter expertise that improves decisions, builds consensus around important investments/roadmaps, and impacts high-level business metrics
Oversight: Effectively drives progress with little to no direct involvement from leadership. Proactively resolves cross-functional challenges and escalates with frameworks and recommendations
Leadership: Forms and leads self-sustaining cross-functional teams with little leadership involvement. Resolves ambiguity and rapidly changes course when needed
Coordination: Sets priorities, leads projects across organizations, and proactively improves operational efficiency
Broader Impact: Improves the PM function or org-wide capabilities, including contributing to learnings to scale AI

Qualifications

10+ years Product Management and/or Product Design
10+ years of experience **partnering with engineering, design, and user research teams to deliver technical products**
Experience navigating through the full product life-cycle, integrating customer feedback into product requirements, driving prioritization, and pre/post-launch execution
Critical thinking/analytical leadership experience
Experience presenting to executive audiences
BA or BS in Computer Science or related field Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience developing product solutions for analytical modeling of supply chain and capacity decision making
Deep background in data center infrastructure, capacity planning, and/or server demand planning for technology companies. Candidates with capacity management experience from adjacent domains (e.g., cloud, networking, supply chain) will also be considered
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)