Engineering Manager - Strategic Infrastructure Capacity Planning

Meta; Bellevue, Menlo Park, Boston, New York (WA, CA, MA, NY); On-site; USD 210,000 - 270,000; Full time

Job summary

Meta is seeking an Engineering Manager to lead the Capacity Engineering team, focusing on site-wide performance and capacity optimization at strategic levels across products and infrastructure. You will grow a team of engineers, balance service, infrastructure, financial, and business constraints, and work with executive leadership on capacity scenarios for future investments.

The role involves managing billions in annual spending and applying AI-enabled optimization to large-scale data centers

Qualifications

• BS degree in Computer Science, Operations Research, or related field, or equivalent practical experience.
• 8+ years of engineering experience, including 3+ years of people management.
• Experience recruiting and leading technical teams.
• Experience with capacity modeling and infrastructure planning.

Responsibilities

• Lead, coach, and grow the Capacity Engineering team.
• Develop and optimize long-range infrastructure capacity plans.
• Collaborate with executive partners to assess capacity scenarios and investments.
• Apply quantitative methods to infrastructure planning and optimization.

Skills

People management

Engineering leadership

Executive collaboration

Quantitative analysis

AI integration

AI ethics

Strategic planning

Budgeting

Distributed systems

Capacity planning

Education

BS degree in Computer Science/Operations Research

Job description

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!

• 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