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Leverage technical understanding of interdependencies across - network, DC and server - hardware supply chain & deployments to drive a converged capacity-delivery outcome for Meta's AI large clusters
Serve as consolidated voice and source-of-truth to customer organizations and internal leadership on large cluster, supply chain status
Develop and implement mid- to long-term cluster delivery strategy for Meta and Meta's supply chain partners. This includes (a) cross-team product coordination, (b) cluster optionality and contingency plans, (c) cluster delivery staging and logistics and (d) cluster demand feasibility models
Identify, flag, and coordinate the response to major technical, material, financial, and information risks impeding cluster delivery
Partner with the planning team on finalizing demand and running supply scenarios. Partner with the sourcing team on commercial readiness of suppliers, and the NPI team on new hardware introduction. Lastly, partner with the manufacturing & delivery teams, and manage launch, manufacturing and deployment of hardware for large clusters
Engage as needed with supplier's material, production, and technical teams to track, consolidate, and de-risk major challenges across large cluster delivery
Develop and maintain critical-path simulations, engineering economic estimates, and contingency plans in order to ensure cluster product delivery, on-time, and within acceptable budgetary guidelines
Maintain current knowledge of the technology and industry trends for large clusters. Work cross functionally to define future technology directions with outsourced manufacturing suppliers
Requirements
Blend of technical and operational experience to understand the relationship between technical roadmap, demand/supply, manufacturing and negotiations
5+ years of supply chain centric technical experience in hyperscale data centers, semiconductor industry, automation/robotics and/or associated industries
BS in Engineering, Suppl Chain or related technical field or equivalent combination of education
Knowledge of technology roadmaps and launch & scale of hardware systems
Proven experience moving from strategy to execution and delivering results
Interpersonal and communication skills with experience influencing, negotiating, building consensus and making strategic decisions
Proven experience interfacing with and establishing relationships with leadership at suppliers or customers
Nice to have
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience interfacing with internal & external partners in an entrepreneurial and cross-functional environment, requiring a latitude for independent judgment while coordinating people and technical resources
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Master's Degree in Business or Engineering
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies