Director of Engineering, Capacity Management (Ads)

We are looking for a Director of Engineering to lead capacity management for the Ads organization at Meta. You will own the standard for how Ads platforms plan, attribute, and govern capacity, and you will build the shared foundations, telemetry, and central processes that make that standard real: rate cards and resource pricing, demand-to-fulfillment planning, usage attribution, launch and quota governance, efficiency validation and clawback, and regression management. The work spans large-scale distributed systems, data infrastructure, and ML serving and training infrastructure, and it requires fluency in both the technical and the financial sides of the problem.

This is a program leadership role. You will own the end-to-end outcomes of Ads Platform Capacity; that every change at the ads level is attributed and charged to the right party, and that platforms can fulfill and claw back capacity reliably. You will lead this program across 10+ platforms, with teams inside those platforms - and the platform leads themselves - formally part of the program and accountable for delivering their part. You will distribute the headcount from a central pool to those platform organizations that are directly accountable for their platform outcomes. You will directly lead a team of senior engineering managers and senior individual contributors, and drive the rest of the program through shared standards, metrics, infrastructure, and the headcount you allocate.

We're looking for a leader with deep infrastructure credibility, experience communicating strategy and influencing decisions with senior and executive stakeholders, and a track record of driving multi-org programs where they owned the outcome without owning the headcount.

Responsibilities

Set and drive the long-term technical strategy and roadmap for ad's capacity management, efficiency, and attribution
Build, manage, and support a team of senior engineering managers and senior individual contributors
Define the capacity maturity model standards that ads platforms are measured against, and drive adoption across approximately ten platform organizations
Own the end-to-end outcomes of the Ads capacity management program: complete attribution and chargeback of Ads-level capacity changes, and reliable fulfillment and clawback across platforms. Build the tooling and telemetry that replace manual tracking, so capacity consumption and efficiency gains are measurable and enforceable
Partner with platform, infrastructure, Finance, and Product Area leaders to agree on roles, responsibilities, and headcount accounting, and to close identified capability gaps
Frame infrastructure investment in terms of dollars, ROI, and risk for senior engineering and business leadership
Identify new opportunities, risks, and priorities for the organization, and establish effective strategies to execute against them
Foster a culture of rigorous execution and high standards for engineering quality
Uphold the principles of respect, integrity, collaboration, and innovation

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
12+ years of experience in software engineering, infrastructure, or a related technical discipline
7+ years of engineering management experience, including managing engineering managers
Experience leading large-scale infrastructure efforts, such as capacity management, fleet or cloud infrastructure, distributed systems, or large-scale platform engineering
Experience leading a large cross-organizational program (100+ people across multiple organizations) where you owned the end-to-end outcome and held partner organizations accountable for their deliverables
Experience allocating headcount or investment across organizations that you do not directly manage, and governing the outcomes it buys
Experience in influencing and aligning senior engineering and cross-functional leaders, including at the VP level
Experience framing technical investments in business terms, including cost, ROI, and risk
Experience in recruiting, building, structuring, and leading technical organizations, including performance management
Ability to tackle problems ranging from technical implementation to strategic planning
Excellent collaboration and communication skills to navigate complex, cross-functional environments Experience in influencing company-level strategy or investment decisions
Experience with accelerator fleets, capacity planning, or resource scheduling for ML training or serving
Experience with large-scale ML infrastructure, ranking, or recommendation systems
Experience in owning capacity allocation, quota, entitlement, or chargeback and showback systems at scale
Exposure to adjacent disciplines such as finance, billing, or compliance systems
Experience in advertising domains