Product Manager, Infrastructure Capacity Planning

Meta•Menlo Park, CA

3d•$205,000 - $277,000

About The Position

Meta's Infrastructure organization provides the backbone for the company and supports the growing demand of its social media products and AI initiatives. 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. You will plan and optimize infrastructure resources, set capacity targets, and coordinate cross-functional teams across engineering, data science, finance, supply chain, and data center construction to meet those targets. You will partner with product teams across Facebook, Instagram, WhatsApp, and monetization to align infrastructure investment decisions with business outcomes amid rapid AI growth and adoption of new hardware. The position includes executive-level engagement and the opportunity to build enduring systems at scale. The role calls for independently identifying significant opportunities, applying subject-matter expertise to improve decisions, building consensus around important investments and roadmaps, and influencing high-level business metrics. You will drive progress with little direct leadership involvement, resolve cross-functional challenges, lead self-sustaining teams, and adjust direction as priorities change. You will also contribute to the effectiveness of Product Management and broader organizational capabilities, including learnings that help scale AI.

Requirements

10+ years of Product Management and/or Product Design experience.
10+ years of experience partnering with engineering, design, and user research teams to deliver technical products.
Experience navigating the full product life cycle, integrating customer feedback into product requirements, driving prioritization, and managing pre- and post-launch execution.
Critical thinking and analytical leadership experience.
Experience presenting to executive audiences.
BA or BS in Computer Science or a related field.

Nice To Haves

Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience developing product solutions for analytical modeling of supply chain and capacity decision-making.
A deep background in data center infrastructure, capacity planning, and/or server demand planning for technology companies; candidates with capacity management experience in adjacent domains such as cloud, networking, or supply chain will also be considered.
Ongoing AI skill development, such as prompt/context engineering or agent orchestration, and staying current with emerging AI technologies.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.

Responsibilities

Proactively identify important problems to solve in support of competitive, strategic, customer, and company goals.
Build a coherent strategy and roadmap for addressing problems, with measurable objectives.
Facilitate information flow among stakeholders and build consensus around vision, priorities, and decisions.
Drive, track, and document progress against roadmaps.
Set a high quality bar for the product area and hold teams accountable to it.
Support recruiting initiatives, including interviewing, to strengthen the organization and Product Management.
Operate effectively amid ambiguity and adapt to shifts in company priorities.
Foster an environment where teams can advocate for robust points of view while working toward consensus.
Independently identify significant opportunities, contribute subject-matter expertise, build consensus around investments and roadmaps, and impact high-level business metrics.
Drive progress with little to no direct leadership involvement, proactively resolve cross-functional challenges, and escalate with frameworks and recommendations.
Form and lead self-sustaining cross-functional teams, resolve ambiguity, and change course rapidly when needed.
Set priorities, lead projects across organizations, and proactively improve operational efficiency.
Improve Product Management or organization-wide capabilities, including contributing learnings to scale AI.