About

I'm Maggie Zhuang — an AI Research Product Manager at Meta, where I work on ranking models that power recommendations across Instagram and Facebook Reels and Feed, reaching billions of users worldwide.

My career spans over a decade of building at the intersection of engineering and product, progressing from software engineer to one of tech's most challenging PM roles in AI and ML platforms.

Career Journey

AI Research PM — Meta (2025–Present)

Leading product strategy for ranking models that drive content recommendations across Instagram and Facebook Reels and Feed. Working at the frontier of recommendation systems and AI research, where model improvements translate directly to experiences for billions of people.

PM, GenAI/ML Platform — Intuit (2024–2025)

Built Intuit's AI-native application experience and drove adoption of the GenOS platform — the company's centralized generative AI infrastructure. Designed agentic workflows that automated complex SMB tasks, bringing the power of large language models to millions of small businesses.

Principal PM — Cash App / Block (2023–2024)

Led product strategy for Cash App's Data & ML Platform, enabling data-driven product development across one of fintech's most widely used consumer apps.

Staff PM — Twitter (2020–2023)

Led the ML & Data Platform team, including Twitter's Feature Store and the migration of offline ML and data workloads from private data centers to Google Cloud Platform. Negotiated a ~$1B GCP contract achieving up to 92% discount on certain products — transforming Twitter's infrastructure economics.

Senior PM — AWS (2016–2020)

Group PM for AWS's managed database portfolio, including Amazon ElastiCache, RDS, Elasticsearch Service, and DynamoDB. Drove pricing strategy, feature roadmaps, and go-to-market for services used by hundreds of thousands of customers. Gained deep expertise in cloud economics and infrastructure at massive scale.

PM — Cisco (2013–2016)

Product manager for cloud and virtualization platforms, bridging the transition from traditional networking to software-defined infrastructure.

Senior Software Engineer — EMC (2007–2011)

Started my career as a software engineer building enterprise storage systems — an experience that gave me the deep technical foundation that continues to inform my product thinking.

Education

MBA — Duke University, Fuqua School of Business
MS, Computer Science — Beijing University of Posts and Telecommunications
BS, Computer Science — Shandong University

What I Write About

Cloud Economics & Infrastructure — After years in the trenches of cloud pricing at AWS and negotiating billion-dollar contracts at Twitter, I write about the unit economics that most teams overlook.

AI/ML Platforms & Recommender Systems — From building Feature Stores at Twitter to GenAI platforms at Intuit to ranking models at Meta, I share insights on what it takes to build ML infrastructure at scale.

Data Strategy & Platform Building — Lessons from building and scaling data platforms across some of tech's largest companies.

My Approach

I believe the best product managers are deeply technical without being technologists. My path from software engineer to AI Research PM has taught me that understanding the systems — really understanding them — is what separates good product decisions from great ones.

I go by magicmag online — a name that reflects my belief that great products feel like magic to their users, even when the underlying systems are anything but.