Austin Chiang is a software engineer with 13 years of experience building large-scale data and integrity systems across major consumer platforms and fintech. He has worked on Facebook’s social graph query language—contributing optimizer improvements that saved the company tens of millions—and built machine learning and safety infrastructure at Instagram to automatically surface and mitigate policy-violating content. At Plaid he focused on product infrastructure spanning orchestration, indexing, and customer-facing querying of bank data, and he continues evolving his craft at Zip. Austin combines deep systems and data engineering expertise with a product-minded approach that abstracts complexity for engineering velocity. He is comfortable working across the full stack of storage, indexing, query planning, and ML-enabled integrity features. Based in the Bay Area and trained at the University of Waterloo, he brings both large-fleet impact experience and practical cross-team delivery skills.
13 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Software Engineering, Bachelor's degree, Software Engineering at University of Waterloo
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