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, Seattle, Washington D.C., Raleigh, London, and Amsterdam.

Plaid’s Connectivity team builds and operates the network that powers open finance. The Supply & Traffic team owns how data supply enters Plaid’s network and how Plaid’s traffic to financial institutions is managed and optimized, so every Plaid product is built on data that is complete, fresh, and cost-effective to retrieve.

Responsibilities:

• You will lead a team of 7 engineers, ranging from junior to Staff and including an ML engineer, developing them through clear goal setting, coaching, and feedback.
• You’ll define and drive the long-term strategy for this focus area, in close partnership with technical and product leaders across Plaid.
• You’ll collaborate with cross-functional partners to identify high-leverage opportunities, shape the roadmap, and dive deep into technical design and execution details to ensure consistent delivery of high-impact business outcomes.
• You’ll lead the transition of traffic management and optimization into the team in early 2027 and own its roadmap across charged access and first-party initiatives.
• You’ll drive automation and AI/ML-powered approaches to discovering new data (Constellation) and to deciding how and when Plaid retrieves it.
• You’ll uphold a high bar for technical quality and delivery velocity, leading by example..
  Qualifications:
• 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management.
• 1+ years of engineering management experience
• Deep experience designing scalable, reliable architectures that support real-world products at scale.
• Experience building or leading teams that ship ML- or AI-driven systems in production.