Meta is seeking a leader to join the Capacity Planning Optimization Engineering team to lead our Capacity Planning process design and execution.
You will build and optimize infrastructure capacity planning processes and tools covering all of Meta, in one of our largest transformations of how we plan and manage infrastructure capacity. This is a hands on leadership role, interfacing with executive leadership at the company to run our infrastructure Capacity Planning processes. Although this is not a software engineering role, you will also design and contribute to planning software systems to increase planning efficiency and quality.
You will be in one of the most cross functional roles at the company, with the opportunity to work with a variety of engineering and business teams at the intersection of all Meta products and services (Facebook, Instagram, WhatsApp, etc), all physical infrastructure (Servers, Data Centers, Network), and product business goals (AI, Metaverse, etc). You will be uniquely positioned to optimize these capacity plans at the most strategic levels with company level impact, with your output used at the CxO level for the most important decisions at the company, as well as providing execution guidance for infrastructure and product teams.
To do this, you will partner across technical and business orgs to design the right solutions and lead engineers to build effective technical and process solutions to transform Meta's capacity planning process to be software driven, highly flexible, agile, and ROI Driven. You will connect business strategy with software-driven modeling of detailed service, platform, and infrastructure considerations for executable plans.
This position is full-time.
Responsibilities
- Own infrastructure capacity planning for all of Meta: all software products/services and plans for how to scale server and data center resources most efficiently
- Partner across the engineering technical landscape to optimize at the intersection of hardware, infrastructure, and software. Work closely with software service owners, Production Engineering, Server Hardware Engineering, Server Supply Chain, Network Engineering, Data Center Design, Operations, and Planning teams to find optimal ways to scale our infrastructure and place our services
- Design and contribute to analytical models to connect business strategy with detailed technical execution including regional and temporal bin-packing, optimal service placement, traffic shifts and service migrations, efficient hardware refresh, etc
- Effectively lead company-wide Capacity Planning business processes across technical and non technical contributors while delivering the most complex parts yourself
- Partner with Finance and business teams to balance cost efficiency with technical and product considerations
- Work cross-functionally to define problem statements, collect data, build software driven models and make recommendations to drive change and optimization at the company level
Minimum Qualifications
- Experience with planning for large-scale technical infrastructure and distributed systems
- Demonstrated success leading large technical infrastructure planning projects and initiatives. Demonstrated success leading large technical infrastructure planning projects and initiatives, including defining goals, managing ambiguity, and leading other engineers and non-technical contributors
- Demonstrated success working with executive level audiences and partners
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, relevant technical field, or equivalent practical experience
- Experience programming in Python, C++, or similar languages
- 10+ years of experience in Engineering, Data Science, or Operations Research 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)
- 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)
- Experience and interest in building "Zero to One" - building systems and process from scratch with ambiguous requirements and goals
- Experience with mathematical optimization and solvers
- Experience with technical infrastructure planning or capacity planning
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies