This position will work with cross-functional teams in Meta's Infrastructure organization to enable Meta's AI applications and use cases on new AI hardware platforms and large-scale AI clusters. This position would focus on synthesizing and communicating user and customer-team requirements, architecting the right middleware stack, leading software design and software enablement efforts, and ultimately on achieving effective deployment of complex AI training and inference workloads across a set of AI platforms. In close collaboration with engineering and cross-functional partners, this person will lead programs aligned with key business priorities. On a day-to-day basis this will involve identifying problems that need to be solved, developing solutions, technical troubleshooting, creating roadmaps and other collateral, defining milestones, quantifying success metrics, driving technical program execution, and communicating with diverse stakeholders. They will work most closely with Software Development teams in Infrastructure including the PyTorch framework team and hardware specific software teams as well as more broadly with Infrastructure Hardware, Capacity Planning, Data Center, Network Infrastructure and Infrastructure Silicon and Systems organizations. Meta's Infrastructure Engineering organization is ultimately responsible for the growth, management, and 24x7 upkeep of all Meta's products and services.

Responsibilities

Collaborate with Engineering and business owners to define program requirements, set priorities, and establish scope, which includes defining the roadmap and long-term strategy of the teams that you are partnering with
• Align with application and end-customer focused technical teams on software and system requirements and schedule
• Create execution strategies and build plans for the full stack software development
• Ensure lower layer components like libraries, tooling, provisioning software, operating system fully enable applications and datacenter operations
• Develop and drive a software benchmarking, analysis and optimization strategy for new hardware platforms
• Lead migration of existing AI software applications to enable critical use cases
• Own end-to-end overall program success spanning developmental phases (requirements, analysis, design, testing, implementation, operations), organizations (software, hardware, capacity, operations, network, sourcing) and locations worldwide
• Build strong and aligned program teams to efficiently deliver on shared goals
• Define and track key metrics and key quality and performance indicators and drive cross functional execution of program deliverables
• Develop and own communication plans to effectively and proactively communicate program status, issues, and risks to stakeholders
• Manage and drive strategic vendor engagement and deliveries
• Manage cross functional dependencies, risks, and changes effectively by optimizing scope, schedule, and resources accordingly
• Perform risk assessment, risk mitigation and change management on projects
• Proactively identify and analyze complex, long-term, critical infrastructure problems with engineering leaders and stakeholders
• Drive internal process improvements across multiple teams and functions

Minimum Qualifications
• B.S. in Computer Science, Electrical Engineering or a related technical discipline, or equivalent experience
• 12+ years of software engineering, systems engineering, hardware engineering or technical product/program management experience
• Experience delivering complex tech programs and/or products from inception to delivery
• Knowledge of user needs, gathering requirements, and defining scope
• Experience operating autonomously across multiple teams, demonstrated critical thinking, and experience driving technical strategy or direction
• Communication experience and experience working with technical management teams to develop systems, solutions, and products
• Organizational, coordination and multi-tasking experience
• Analytical and problem-solving experience with large-scale systems
• Experience establishing work relationships across multi-disciplinary teams and multiple partners in different time zones

Preferred Qualifications
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Understanding of AI algorithms and techniques
• Experience working with hardware-specific software optimization
• Experience working with capacity planning, migration and turn-up
• Experience with high performance or AI training clusters
• Experience with data center architecture and deployment
• Understanding of Graphics or AI accelerator hardware architecture
• Experience with system analysis and hardware-software co-design
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Understanding of AI software development life cycle
• Understanding of scientific or technical computing techniques
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies