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Staff Software Engineer, PEO Growth

Gusto San Francisco, CA - HybridUSD 163,000–204,000 / yearLead

Key requirements

  • Typescript
  • React
  • Compliance
  • Security
About Gusto At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve. All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy . AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process. About the Role Gusto is building a PEO (Professional Employer Organization): a product where Gusto becomes a co-employer for small businesses, taking on payroll, benefits, workers' compensation, and HR compliance so owners don't have to assemble it themselves. It's one of the biggest strategic bets in the company. As a Staff Engineer on PEO Growth, you'll own the path from how a business discovers PEO all the way to getting the business fully set up. The decisions you make here shape whether a small business can adopt one of the most consequential products we've ever shipped, or give up halfway through. About the Team PEO Growth owns the customer experience of adopting the PEO — the end-to-end journey that takes a business from interested to fully up and running. Much of what that journey depends on is built by other teams across Gusto, so our job is to make it feel like one coherent product rather than a series of handoffs. That makes the work as much cross-team design and negotiation as it is code, and it means you'll have real influence over how the experience gets shaped, not just how it's implemented. The team is a pod of engineers, product manager, and designer with a bias towards building and shipping. Here's what you'll do day-to-day Own the PEO Onboarding experience end to end — how a business learns about the PEO, commits to it, and gets set up on it — and be accountable for whether customers make it all the way through. Set technical direction: turn ambiguous product bets into designs, sequencing, and durable abstractions that hold up as the product and its audience grow. Build in a regulated domain where quality and accuracy is critical. Partner across other app teams to integrate their domains into one coherent journey, and negotiate the seams when ownership is unclear. Use AI as a normal part of how you work — coding agents, review, debugging, and codebase exploration — and help build AI-assisted guidance into the onboarding experience itself so customers get unstuck without waiting on a human. Instrument the funnel and make decisions from it: define what "onboarding is working" means, measure it, and use experiments rather than intuition to decide what to change. Raise the engineering bar in a fast-moving area — reviews, testing strategy, observability, and the judgment calls about where to build carefully and where to move fast. Here's what we're looking for 8+ years of professional software engineering experience, including meaningful time owning customer-facing product surfaces in a large production codebase. Strong full-stack range: comfortable in a mature server-side codebase and in a modern component-based frontend. Ruby on Rails and React/TypeScript are what we use and are desirable, but we care more about depth than the specific stack. Demonstrated AI fluency : you already use AI tooling in your day-to-day engineering work, can speak concretely about where it helps and where it doesn't, and you keep up as the tooling changes. High ownership in ambiguity.

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