Technical Program Manager, AI Network Infra
Meta

This position will play a critical role in driving end-to-end AI product introductions and AI operations initiatives supporting Meta's growing AI/HPC infrastructure for our Family of Apps . They will be responsible for overseeing the entire program lifecycle, from concept to planning to execution to monitoring, ensuring successful delivery and implementation. This includes collaborating with cross-functional Engineering teams to define scope, goals, and timelines, as well as leading the cross functional teams in delivering the business outcomes. They will help solve some of the most challenging networking problems in the industry, drive innovative, creative and ground-breaking solutions & technologies. The ideal candidate will have experience in AI/HPC product development and operations, strong understanding of the Network communications stack for AI solutions, fundamental knowledge of the hardware components, strong program management skills, and excellent communication and leadership abilities. As such,they need to understand the problem space and domain in depth, create roadmaps, prioritize based on impact and drive product development from concept to production. They will operate in a multi-organization landscape.

Technical Program Manager, AI Network Infra Responsibilities:

• Lead technical program management of next-generation Artificial Intelligence/Machine Learning (AI/ML) platform(s) for Meta's Network Infrastructure in a matrix organization covering a range of areas (Data Center, Network, Hardware Systems, Infrastructure Engineering, Software Engineering, Capacity Management) and across multiple physical locations
• 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.
• Manage cross functional dependencies, risks, and changes effectively by optimizing scope, schedule, and resources accordingly.
• Develop and own communication plans to effectively and proactively communicate program status, issues, and risks to stakeholders.
• Partner with cross functional teams to drive technical analysis, design, development, testing, implementation, and post implementation phases.
• Define and track key metrics and key quality and performance indicators and drive cross functional execution of program deliverables.
• Proactively identify and analyze complex, long-term, critical infrastructure problems with engineering leaders and stakeholders.
• Drive internal and external process improvements across multiple teams and functions including reducing the manual efforts through automation.
• Build strong and aligned program teams to efficiently deliver on shared goals.

Minimum Qualifications:

• B.S. in Computer Science or a related technical discipline, or equivalent experience.
• 12+ years of software engineering, systems engineering, hardware engineering, or technical product/program management experience.
• 8+ years experience in delivering Network solutions/Programs for Data Center applications.
• Experience delivering tech programs or products from inception to delivery.
• Experience operating autonomously across multiple teams, demonstrated critical thinking, and thought leadership.
• Communication experience and experience working with technical management teams to develop systems, solutions, and products.
• Analytical and problem-solving experience with large-scale systems.
• Experience establishing work relationships across multi-disciplinary teams and multiple partners in different time zones.
• Understanding of the Network communication stack, Network Hardware (NICs, Optics & Switches).
• Experience Developing & Delivering AI Cluster Solutions for training & inference use cases.

Preferred Qualifications:

• Experience in Network protocols (RoCE, IB, Ethernet).
• Experience working with large scale distributed systems.
• Experience with data center architecture & Deployment.
• Experience working with ODMs and silicon vendors.
• Experience with AI training and inference model deployments to physical infrastructure.

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