Engineering Manager - Strategic Infrastructure Capacity Planning

Meta is seeking an Engineering Manager to join the Capacity Engineering team to focus on site-wide performance and capacity optimization at the most Strategic levels, at the intersection of all Meta products and services, and all physical infrastructure (Servers, Data Centers, Network). This role will focus on leading, coaching, and growing a team of engineers to create and optimize strategic infrastructure capacity plans at various altitudes to balance service, infrastructure, financial, and business constraints, directly managing $Billions of investment per year. We do this primarily by building software and mathematical optimization models, not manual planning. This role will be uniquely positioned to work with our executive team to assess Capacity scenarios for executability, tradeoffs, and impacts for building one of the largest fleets in the world. This is one of the most cross functional roles at the company, with the opportunity to work with a variety of engineering and business teams to power the rapid growth of Meta’s products. You will ensure the right long-range strategic investment decisions are made for our products and infrastructure, including the latest AI and non-AI technologies. You will work with millions of servers, Gigawatts of data center capacity. You will help build one of the largest fleets, powering one of the largest internet services in the world!

Responsibilities

Capacity planning for all of Meta: all software products / services. Develop and analyze business and technical data and what-if scenarios to drive the highest levels of executive decision making around infrastructure / product investments and strategy, up to the CxO level Build and maintain high performing team: Hire and retain high-performing engineers. Own career development and health of team to ensure continued growth in capability over time Assess team performance on an ongoing basis: address under-performance, recognize and promote performance Maximize the conditions for the team's success: ensure clarity in team vision, priorities, roadmap and key business context. Develop, maintain, and if needed, fix relationships with cross functional partners across technical and business functions Effectively navigate complex tradeoffs and relationships to balance solving for team, cross-functional partner / stakeholders, and Meta company priorities Connect the dots: Identify capacity-related issues at all layers of the stack and proactively work across technical and business teams to define and implement solutions Drive technical discussions: influence technical design and process in partnership with team, review key team outputs. Take on some technical IC work and have strategic influence technically Develop and maintain effective partnerships across technical and business teams including software service owners, Production Engineering, Server Hardware Engineering, Finance, Server Supply Chain, Network Engineering, Data Center, Operations, and Planning teams to find the most optimal ways to scale our infrastructure and place our services

Qualifications

BS degree in Computer Science, Operations Research, or other technical field, or relevant practical experience 8+ years of engineering work experience, including 3+ years of hands-on engineering people-management Demonstrated experience with recruiting, developing, and leading technical teams Demonstrated success in managing challenging relationships and competing priorities with executive level partners or customers Experience applying quantitative and analytical methods to infrastructure planning, capacity modeling, or similar problem domains Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience with strategic planning, budgeting and finance Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience and demonstrated success with distributed systems and infrastructure planning at scale