Senior Staff Software Engineer, Growth Onboarding

Responsibilities

• Own meaningful slices of the signup-to-activation experience end to end — from data model to UI — and ship measurable improvements to how quickly and reliably new customers get up and running.
• Invent and prototype net-new, 0-to-1 experiences — bringing your own ideas for how AI can reimagine onboarding.
• Partner directly with Product, Design, and Data to frame problems, form hypotheses, and validate them with real customers in weeks, not quarters.
• Identify where AI meaningfully removes customer effort (and where a simple form is better), and build those experiences thoughtfully into the flow.
• Design onboarding as modular, reusable building blocks so new entry points into Gusto can be added quickly without rebuilding the foundation.
• Raise the engineering bar through pragmatic technical direction, high-quality code, strong reviews, and mentoring engineers around you.
• Make sharp scoping calls under a time box — shipping the simplest version that proves or disproves an idea, then iterating.

Requirements

• 10 - 12+ years of software engineering experience, including building and shipping customer-facing products at scale.
• A product-minded engineer who starts from the customer problem and the metric that matters, not just the ticket — and who can operate independently across product, design, and data partners.
• Demonstrated ability to move quickly and execute with high quality: someone who ships, measures, and iterates rather than waiting for perfect certainty.
• Experience applying AI/LLM capabilities to real product problems — with the judgment to know where it adds value and where it adds noise — and a habit of using AI tools to work more effectively.
• A founder mindset: high ownership, comfort with ambiguity and greenfield problems, and a bias toward action and outcomes over output.
• A track record of raising the bar for teams around you — through technical leadership, mentorship, and setting standards others follow.
• Strong full-stack fundamentals and the versatility to work wherever the problem is (front end, back end, data).

Nice-to-Haves

• Experience with AI/LLM tools and applying them to product experiences.
• Versatility across the stack, including front end, back end, and data layers.
• Prior experience in growth, onboarding, or building 0-to-1 features.

Compensation

• Cash compensation targeted at $223,000/yr to $278,000/yr for San Francisco, CA.
• Final compensation packages will include equity (RSUs) and benefits.
• Final base salary offerings will be determined by multiple factors including candidate experience and expertise.