About this role
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’s Finance team is rebuilding planning, forecasting, and analysis with AI at the center. As Staff FP&A AI Architect, you’ll design and lead the technical and process architecture that turns FP&A from a manual, spreadsheet-driven cycle into an automated, insight-generating function. You’re a hybrid: deep enough in finance to understand driver-based planning, variance analysis, and board reporting, and deep enough in data and AI to design the systems that automate them. You’ll partner with the CFO org, FP&A, Accounting, Data, and Engineering.
About the Team
This is a new role on the Enterprise AIT team, which drives the intelligent transformation of Gusto’s enterprise systems by integrating AI, automation, and advanced analytics across internal applications. The team works closely with Finance, Business Ops, IT, and Security, and this role brings dedicated AI architecture capacity to FP&A and the CFO org.
What You’ll Do
• Set the strategy: Define the multi-year architecture and roadmap for AI-enabled planning, forecasting, and reporting, prioritizing use cases by value, feasibility, and risk.
• Build forecasting systems: Architect driver-based, ML-assisted forecasts for revenue, headcount, opex, and cash, combining statistical models with LLM workflows and benchmarking against human forecasts.
• Automate analysis: Build agentic workflows for variance commentary, flux analysis, scenario modeling, board and QBR narratives, and ad-hoc “ask the numbers” questions.
• Own the finance data foundation: Work with Data Engineering on governed data models connecting the GL, billing, CRM, HRIS, and planning tools, so AI outputs are traceable and auditable.
• Embed controls and trust: Establish evals, human-in-the-loop checkpoints, lineage, and audit trails that meet SOX, security, and privacy requirements.
• Evaluate and select tools: Drive build-vs-buy decisions across planning platforms, LLM providers, and orchestration frameworks.
• Lead through influence: Mentor analysts and engineers, create reusa