Staff Software Engineer, Retirement AI

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:

You’ll be a key engineer helping us ship real, user-facing AI at Gusto Retirement. This role is all about bias to action: owning problems end-to-end, getting working software in front of customers, and iterating quickly. You’ll work closely with a small, senior team to implement language-model-powered experiences. If you like being hands-on, making pragmatic technical decisions, working closely with product & design partners, and turning ideas into production features, you’ll be a great fit.

About the Team:

We’re a small, focused AI product team building practical, high-impact experiences to help people save for retirement at Gusto Retirement. The team is senior, collaborative, and very execution-focused—PMs bring strong ideas, and we own the execution fully. We work closely with product, design, and partner engineering teams, but keep tight ownership of our priorities and roadmap.

Here’s what you’ll do day-to-day:

• Design, build, and ship production features that use large language models to solve real customer problems.

• Implement and integrate LLMs (prompting, tool loops, evaluation, monitoring, etc).

• Make pragmatic architecture decisions, de-risk tricky areas, and keep the work unblocked.