Software Engineering Manager, Growth

About the Role

As Gusto transitions to an AI-native company, this role will help shape how intelligence is embedded across our Growth platform — from acquisition to onboarding to expansion. You’ll lead engineering efforts that make our systems adaptive, data-driven, and intelligent by design.

This means building not only for scale and reliability, but for learning and continuous optimization — where every part of the funnel can reason, predict, and personalize. You’ll operate at the intersection of Growth systems, AI capabilities, and platform evolution to help unlock Gusto’s next phase of sustainable revenue growth.

About the Team

We’re accelerating Gusto’s revenue growth by innovating, designing, and experimenting with different upsell paradigms such as ML-based recommendation systems, embedded contextual nudges, user intent-driven upsells, human-and-AI hybrid outbound upsells and continuously improving Gusto Store and checkout experience.

Our focus is shifting from deterministic user journeys to intelligent growth systems — ones that understand intent, tailor experiences, and continuously improve through data and feedback.

We’re looking for a strategic and motivated engineering leader to empower and scale the engineering teams that are building Gusto’s next big thing!

Here’s What You’ll Do Day-to-day

• Build and foster an inclusive, collaborative, and impact-oriented culture
• Conduct regular 1:1s with your team members to support their continued growth and learning
• Collaborate with our product management and design teams to define, iterate, and execute on initiatives contributing to Growth’s roadmap to drive revenue growth.
• Partner with Product, Design, Data and others within and outside your team
• Help build and manage team processes and create a culture that enables the team to do its best work
• Provide and receive mentorship and peer support
• Champion AI-native patterns in Growth systems — designing for learning loops, feedback-driven iteration, and safe model usage in customer-facing contexts.
• Help establish best practices for experimentation, evaluation, and observability in AI-augmented Growth experiences.
• Partner with cross-functional teams to tackle complex and ambiguous problems, translating them into engineering solutions that drive our customer acquisition and ACV expansion platform forward.
• Collaborate with AI platform and data science teams to integrate model-driven insights into Growth workflows — such as lead scoring, onboarding personalization, intelligent upsell recommendations, and AI/ML-driven comms platform.

Here’s What We’re Looking For

• 8+ years of professional software development experience, preferably in B2B software and/or growth engineering
• At least 2 years empowering Product or Growth engineering teams
• Preference for experience building and maintaining onboarding funnels, checkout flows, upsell/cross-sell systems or other complex multi-step workflows
• Experience managing and mentoring a software development team
• Ability to work iteratively with data and experimentation driven development, and a record of driving impact reflected in metrics and customer sentiment
• Experience working cross functionally with product, design, data, sales, support, and marketing
• Curiosity and ability to operate in an AI-native environment — integrating intelligence, automation, and experimentation into how we grow the business.
• Experience in highly cross-functional environments for highly complex products.
• Experience in scaling Engineering organizations.
• Nice to have:
• Experience leading a team on designing or implementing product experiences incorporating ML and AI — from recommendations to intelligent onboarding or personalization systems.
• Experience in experimentation and user experience optimization.
• Experience working closely with Revenue teams.

Our cash compensation amount for this role is targeted at $163,000-$204,000 in Denver, $178,000-$223,000 for Los Angeles and most remote locations, $197,000-$247,000 for San Francisco, New York, and Seattle. Final offer amounts are determined by multiple factors including candidate experience, level, and expertise and may vary from the amounts listed above.