Plaid
Staff Software Engineer - AI & Intelligent Tooling
San Francisco HQ · Staff+
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About the role
- This is a hands-on role with significant ownership, where success is measured by real adoption, reliability, and improvements to developer experience.
Responsibilities
- Design, build, and operate internal tools and services used by Plaid's engineers.
- Own systems end-to-end, including production support and iterative improvement.
- Collaborate with teammates and stakeholders to deliver practical, high-impact solutions.
Requirements
- 8+ years of professional software engineering experience.
- Hands-on experience using AI-powered developer tools.
- Track record of setting technical direction and leading through influence.
- Familiarity with CI/CD, cloud infrastructure, or observability tooling.
- Experience building developer tooling, internal platforms, or infrastructure.
- Exposure to developing AI systems, automation, or agentic workflows.
- Strong problem-solving and collaboration skills.
- Strong interest and excitement in leveraging AI to meaningfully improve developer productivity and engineering velocity for a broader engineering organization.
Skills
- Plaid powers the tools millions of people rely on to live a healthier financial life.
- Plaid's network covers 12,000 financial institutions across the US, Canada, UK and Europe.
- Plaid is evolving into an AI-first company, and Intelligent Tooling sits at the center of that transformation.
Compensation
- Additional compensation in the form(s) of equity and/or commission are dependent on the position offered.
Company info
- Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.
- When we are successful, engineers across Plaid will delegate lower-leverage work to AI agents, move faster with confidence, and spend more of their time designing and inventing for customers.
- Our mission at Plaid is to unlock financial freedom for everyone.
This listing is sourced directly from Plaid's careers page and normalized into a canonical job model.