Enterprise AI Architect

Join to apply for the Enterprise Application AI Architect role at Gusto
.

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff—like payroll, health insurance, 401(k) s, and HR—so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we’re proud to support more than 400,000 small businesses across the country, and we’re building a workplace that represents and celebrates the customers we serve.

As the Enterprise Applications AI Analyst, you will lead the integration of AI and automation across Gusto’s enterprise applications ecosystem, transforming how internal systems connect, communicate, and operate. Sitting within the IT and Enterprise Applications organization, you will partner closely with Product, Engineering, Finance, People Tech, and Operations to bridge business needs with AI-driven solutions. You will act as the connector between business requirements and AI frameworks, designing Model Context Protocols (MCPs) and AI agents that make enterprise workflows smarter, faster, and more autonomous.

In line with Gusto’s FY26 Enterprise Systems strategy, you will help shift our ERP and Finance systems from reactive workflows to predictive, context-aware, and self-improving platforms, while ensuring security, compliance, and measurable impact. This role combines hands‑on technical execution with strategic systems thinking, using integration fluency, AI literacy, and business empathy to create the connective tissue that allows AI to seamlessly augment enterprise operations.

• Translate business needs into AI workflows by partnering with Finance and Business Operations teams to identify automation opportunities and design agentic workflows that improve decision making and reduce manual effort.
• Develop and maintain Model Context Protocols (MCPs) that securely and reliably connect enterprise systems such as Net Suite, Zuora, and Jira to AI agents, with clear documentation and optimization.
• Create and manage intelligent agents that execute or augment core enterprise processes such as onboarding, billing support, and compliance monitoring using large language models and orchestration frameworks.
• Govern the full lifecycle of MCPs and agents, ensuring adherence to enterprise data governance, privacy, and security standards, including SOX compliance, auditability, and appropriate access controls.
• Measure and optimize impact by defining and tracking KPIs such as automation adoption, efficiency gains, agent accuracy, reliability, and cost performance, and using those insights to guide iteration.
• Enable and influence the organization by partnering with IT, Security, and business stakeholders to build reusable AI frameworks, coach teams on safe and effective AI-driven workflows, and champion AI-first practices across day-to-day operations.

• 8+ years in Business Systems Analysis, Enterprise Applications, or Automation roles, with a track record of delivering impact in complex environments.
• Demonstrated experience building and maintaining integrations across systems such as Jira, Net Suite, or similar, with a strong grasp of APIs, JSON, and RESTful service design.
• Hands‑on knowledge of AI agent frameworks (for example Lang Chain, CrewAI, Semantic Kernel, MCP) and experience designing or maintaining Model Context Protocols or equivalent frameworks.
• Familiarity with leading LLM platforms (OpenAI, Anthropic, Gemini etc.) and practical experience with prompt engineering.
• Proficiency in Python or JavaScript for automation, orchestration, and building modular, scalable AI workflows that translate complex requirements into executable solutions.
• Strong documentation, analytical, and stakeholder communication skills, with the ability to clearly explain tradeoffs and align technical solutions with business needs.
• Passion for building secure, compliant, and explainable AI systems, embedding risk, privacy, and compliance considerations (including SOX and audit controls) into every solution, with a growth mindset and focus on clarity, iteration, and measurable outcomes.