NPI Operations Program Manager

Meta's hardware organization is seeking an experienced New Product Introduction (NPI) Operations Program Manager to lead complex, large-scale hardware programs from early development through mass production. In this role, you will serve as the operational backbone for NPI programs, driving cross-functional alignment across engineering, supply chain, contract manufacturing, quality, and logistics to ensure products launch on time, within cost, and at the required quality bar. You will apply deep NPI expertise to shape program strategy, resolve manufacturing readiness risks, and establish scalable processes that improve how Meta brings consumer hardware products to market.

Responsibilities:

Lead end-to-end NPI program operations for consumer hardware products, spanning prototype builds through mass production ramp, ensuring milestone readiness across engineering, manufacturing, and supply chain functions Define and own the integrated NPI master schedule, identifying critical path dependencies, build readiness risks, and mitigation strategies across contract manufacturing partners and internal teams Drive manufacturing readiness reviews, build readiness gates, and production qualification milestones by coordinating cross-functional inputs from mechanical, electrical, firmware, and operations teams Partner with contract manufacturing and supply chain teams to resolve yield, capacity, and component availability issues that could impact NPI build schedules or mass production ramp targets Develop and maintain program dashboards and executive-level reporting that communicate NPI status, risks, and tradeoffs to leadership and cross-functional stakeholders Establish and refine NPI operational processes, build playbooks, and lessons-learned frameworks to improve program execution efficiency and repeatability across hardware programs Identify and drive resolution of cross-functional blockers involving tooling readiness, test coverage, regulatory certification, and factory qualification timelines Collaborate with quality engineering and reliability teams to track and close open issues from DVT through PVT, ensuring product quality standards are met prior to mass production release Leverage AI-integrated workflows and program management tooling to synthesize build data, track action items, and accelerate decision-making across distributed teams Contribute to organizational NPI strategy by identifying systemic gaps in program execution and implementing interventions that improve overall hardware launch outcomes

Qualifications:

8+ years of experience in NPI program management or operations program management for consumer hardware products Experience leading cross-functional hardware programs through full NPI lifecycle, including EVT, DVT, PVT, and mass production ramp phases Experience managing contract manufacturing relationships and supply chain operations in the context of hardware product launches Experience developing and communicating program status, risk assessments, and tradeoff recommendations to cross-functional stakeholders and leadership Experience identifying manufacturing readiness risks and driving resolution across engineering, operations, and supply chain teams Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience leading NPI programs for consumer electronics, wearables, or mixed reality hardware products at scale Familiarity with factory qualification processes, test coverage strategies, and yield improvement methodologies in high-volume consumer hardware manufacturing Demonstrated use of data analysis or AI-assisted tools to improve program visibility, build readiness tracking, or cross-functional decision-making Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience building or standardizing NPI program management processes, templates, or operational frameworks across a hardware organization Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)