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Director, Product Management - Meta Superintelligence Labs
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Assessing your cultural and operational fit
Product Executive combining deep technical expertise across the full AI stack, from custom silicon to agentic applications—with a track record of scaling 0-to-1 bets into billion-dollar businesses. Defined industry-standard platforms at Meta, Microsoft, and AWS, including leading Azure OpenAI from inception to $1B+ ARR. Adept at bridging research and commercialization, currently spearheading the transition to autonomous agentic AI.
University of Maryland
Bachelor of Science (B.S.), Electrical and Electronics Engineering
N/A – Present
University of Washington
Computer Science
N/A – Present
Meta
Director of Product Management
November 1, 2024 – Present
Stealth AI Startup
Head of Product
April 1, 2024 – November 1, 2024
Seattle, WA
Microsoft
Partner | Head of Product - Azure OpenAI
January 1, 2021 – March 1, 2024
Microsoft
Principal Group Product Manager - Azure AI
May 1, 2019 – January 1, 2021
Amazon Web Services (AWS)
Product management - AWS AI services
January 1, 2016 – May 1, 2019
Greater Seattle Area
AT&T
Director of Product Management
May 1, 2011 – January 1, 2016
Dallas/Fort Worth Area
Motorola Solutions
Systems Engineering
June 1, 2004 – May 1, 2011
Cultural Fit Analysis
The candidate has a strong background in large, established tech companies, indicating an ability to navigate complex organizational structures and contribute to high-impact projects. Their experience with both internal and external-facing products, including open-source efforts (Apache MXNet), suggests adaptability. However, the target role is 'ML Engineer', while the candidate's experience is predominantly in 'Product Management'. This represents a significant mismatch in core function, which could impact cultural fit for an engineering-focused team.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, strategic thinking, and business acumen through their extensive product management roles. Their experience in defining product roadmaps, pricing, and developer experience suggests excellent operational fit for driving ML initiatives. The ability to lead cross-functional teams and manage large portfolios indicates strong collaboration and project management skills.