We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s authoritative source of truth for the user lifecycle: powering recognition, authentication, and the data models behind Plaid’s newest ML-based insights products ( LendScore , Protect , etc.). We build the APIs, systems and data models that let Plaid products deliver user-level intelligence at scale. At the center of our work is the living graph that represents people’s entire financial lives; the largest dataset at Plaid! This links all of Plaid’s users, identities, accounts, and transactions. We operate it reliably at global scale for some of the world’s largest companies, including Google, Meta, Shopify, Square, Robinhood, and Venmo. The team owns 3 core pillars: - The User Graph: Defines Plaid’s global user and maintains the graph linking identities, accounts, and transactions, exposed via internal APIs for product development and ML inference. - The User API: Plaid’s newest API surface, enabling easy multi-product integration and powering fraud prevention, credit decisioning and pre-qualification capabilities, and other data partner insights. - The User Decisioning Layer, which powers returning user recognition and authentication across Link and API-only experiences. We tackle hard problems in identity, graph integrity, and trust so product, ML, and data teams can build reliable fraud, credit, and financial management experiences at U.S. financial network scale.We are a high‑performing group of engineers based in San Francisco and New York, collaborating in‑office.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
501-1,000 employees