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NPI Program Manager
Job in
Menlo Park, San Mateo County, California, 94029, USA
Listed on 2026-11-05
Listing for:
Meta
Full Time
position Listed on 2026-11-05
Job specializations:
-
Engineering
Operations Management, Hardware Engineer
Job Description & How to Apply Below
Meta is seeking an experienced New Product Introduction (NPI) Program Manager to drive the development and delivery of infrastructure hardware that powers Meta's global infrastructure. In this role, you will own end-to-end NPI program execution for hardware — from early-stage concept through mass production. You will partner closely with hardware engineering, supply chain, contract manufacturers, and data center operations teams to ensure that hardware programs are delivered on schedule, within budget, and at the quality standards required to support Meta's infrastructure scale.
- 6+ years of experience in hardware program management, with direct ownership of NPI programs for network, AI, compute, or storage hardware products
- Experience managing cross-functional hardware development programs from prototype through mass production, including EVT, DVT, and PVT build phases
- Experience identifying, tracking, and mitigating program risks across hardware design, supply chain, and contract manufacturing work streams
- Experience communicating program status, risks, and tradeoffs to engineering and operations stakeholders through structured written and verbal updates
- Experience using program management tools and methods to build integrated schedules, manage dependencies, and track deliverables across hardware development programs
- Familiarity with hardware design and qualification processes, including ASIC bring-up, PCB design review cycles, and network system-level testing
- Experience managing NPI programs specifically for hardware in a hyperscale data center or infrastructure context
- 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)
- Background in data analysis and use of program metrics to drive schedule and resource tradeoff decisions across concurrent hardware programs
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience working directly with contract manufacturers and original design manufacturers on hardware build planning, yield management, and production ramp
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