Gusto Staff Software Engineer at Gusto responsible for full-stack development of customer-facing core products. Mentor engineers and scale large Ruby/Rails and Javascript/React applications.
Responsibilities
We're looking for seasoned full-stack software engineers to join the teams behind Gusto's customer-facing products — the features and experiences that small business owners and their employees rely on every day.
As a Staff Software Engineer, you'll operate across the full product lifecycle: shaping features from early spec and design through to launch and long-term iteration. That means writing clean frontend code, designing and building reliable backend APIs, influencing product direction, and taking ownership of what happens after a feature ships.
If you're drawn to work that combines technical craft with real-world impact — helping power the livelihoods of millions using Gusto products — join us!
Here’s what you’ll do day-to-day:
Design, build, and test Gusto core products such as Payroll, Benefits, HR, Retirement, Gusto Money, Gusto Solo, and Gusto Pro, among others
Mentor other engineers to help solve some of the hardest technical problems out there in very complex domains and at a large scale
Help scale one of the largest Ruby/Rails and Javascript/React applications in the world
Collaborate with our Product Management, Data, Design, and Platform Engineering teams to understand customer pain points, come up with solutions, and then prototype, iterate, and launch daily
Build products that our customers genuinely love
Here’s what we're looking for:
Successful applicants typically have 10+ years of software development experience
Experience building scalable solutions that eliminate customer pain; passion for creating memorable experiences for customers
Qualification
Experience building scalable solutions
Required
8+ years of software development experience
Experience building scalable solutions
Experience leveraging AI tools or systems
Experience owning multi-quarter projects
Experience with large scale refactors and performance
Preferred
Curiosity and experimentation with emerging AI frameworks
Applying and sharing best practices to evaluate and scale AI use safely