Senior Staff Software Engineer, Onboarding and Activation Full Time

About the Role:

Getting started on Gusto should feel effortless — the path from "I just signed up" to “my business is set up and running on Gusto” is where small business owners need us most, and where the biggest opportunity to grow the business lives. We're in the middle of the most exciting shift in Gusto's history: reimagining our product as a proactive AI teammate that doesn't just help small businesses, but does the work for them. Most of that opportunity is still ahead of us — which means this role is full of net-new, 0-to-1 problems to invent and build from the ground up. As a Staff Product Engineer on Growth Onboarding, you'll own the experience that turns curious signups into activated, thriving customers — taking friction out of getting started and meeting customers wherever they are, from the web to SMS, WhatsApp, and third-party AI assistants like ChatGPT and Claude — working full-stack and cross-functionally as both a product builder and a founder.

About the Team:

Growth Onboarding owns one of the most consequential moments in a customer's journey: their first experience of Gusto. We're a full-stack, outcome-driven team measured by activation — not features shipped. We move fast, ship prototypes over docs, and partner tightly with Product, Design, Data, and other engineering teams to make onboarding simpler, smarter, and a launchpad for everything a business does next. You won't just be handed a roadmap — you'll help invent it, turning a bold AI product vision into new front doors and experiences that have never existed before. If you want your work to move a top-line number and shape the front door to a company serving 500,000+ businesses, this is the team.

Here’s what you’ll do day-to-day:

• 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, not just implementing a spec handed to you.
• 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.

Here’s what we're looking for:

• 10+ 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 fast 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).

Our cash compensation amount for this role is targeted at $223,000/yr to $278,000/yr for San Francisco. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.