AI Solutions Architect

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  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.

We are building AI-powered, agentic workflows to transform how service operations scale, resolve customer needs, and maintain quality in high-stakes environments. At Gusto, that means designing systems that can earn the trust of small business owners — where a wrong answer or a missed escalation has real consequences.

As an AI Solutions Architect, you will own the end-to-end design and performance of these workflows in production — where models, tools, data, and human judgment come together to deliver outcomes. This is not a traditional architecture role. You will design, prototype, deploy, and continuously improve AI-driven systems that directly impact customer experience and operational efficiency. You will also play a key role in shaping the evolution of our AI platform by identifying capability gaps, prototyping solutions, and informing the primitives required to scale agentic systems effectively.

You will report into the Service Transformation org and work at the intersection of AI governance, service quality, and operational transformation — operating as the connective tissue between Engineering, CX, Legal, and Compliance as Gus, Gusto's AI assistant, scales.

The mission of our Service Transformation (CXT) team is to quickly evolve and scale how Gusto delivers outstanding service experiences and leverages AI to do so. Our team designs the systems, governance frameworks, and feedback loops that allow Gusto's service model to improve continuously, operate reliably, and earn the trust of the customers and employees who depend on it.

• Architect, prototype, and own end-to-end agentic service workflow frameworks, from scoping through production deployment and iteration — including solve and assist targets, HITL protocols, override logic, and downstream quality safeguards
• Analyze SOPs, operational metrics and interaction data to identify and prioritize high-impact automation opportunities based on volume, risk, and customer impact
• Design and implement multi-agent orchestration patterns across tools, data sources, and decision steps within a single end-to-end workflow
• Apply and influence AI platform capabilities in partnership with CoreX (Gusto's AI Platform team) — including orchestration, retrieval, and evaluation — helping define what needs to be built to support production workflows at scale
• Identify platform gaps, prototype workflow-level solutions, and partner with engineering to shape the primitives required for reliable, scalable AI systems
• Serve as the primary CX voice in Legal, Security, Compliance, and CoreX forums — translating CX quality stakes and workflow risk into terms each audience acts on, and ensuring governance requirements are embedded in design, not retrofitted after launch
• Strengthen evaluation frameworks and feedback loops to ensure quality, compliance, and continuous improvement; contribute to Gusto's human evaluation programs and AI governance practices through deep partnership with our internal CX Labs team
• Partner with Data teams to define and track workflow performance — including solve and assist rate, AHT, rework rate, and customer effort score — clearly distinguishing between model-level, workflow-level, and…