Performance & Capacity Engineer - Capacity Planning Optimization(Technical Leadership)

Job description

Meta is seeking a Performance & Capacity Engineer to join the Capacity Planning Optimization Engineering team to lead software systems and process design. You will build and optimize infrastructure capacity planning covering all of Meta, in one of our largest transformations to date of how we plan and manage infrastructure capacity. This is a hands on leadership role, building some of complex parts of the system yourself while leading other engineers and non-technical contributors.

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 strategic levels with company level impact, with your output used at the CxO level for key strategic decisions, 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.

Contribute to building and scaling Meta's global infrastructure and internet services! 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 help build software systems to build scalable, reliable planning systems 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 large engineering efforts while implementing complex parts of the system and process design 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 strategic levels

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 10+ years of experience in Performance, Capacity, or software engineering
• Proficient in Python, C++, or other coding languages and designing large scale software systems
• Demonstrated success leading large engineering projects and initiatives.

Defining goals, managing ambiguity, inspiring and leading other engineers and Demonstrated success leading large engineering projects and initiatives, including defining goals, managing ambiguity, and inspiring and leading other engineers and non-technical contributors Experience with large-scale technical infrastructure and distributed systems

• 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 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience and interest in building "Zero to One" - building systems and processes from scratch with ambiguous requirements and goals
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with mathematical optimization and solvers
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience with technical infrastructure planning or capacity planning