Why This Job is Featured on The SaaS Jobs
This Enterprise Application AI Architect role stands out in SaaS because it focuses on the internal systems layer that underpins subscription businesses, connecting tools like ERP, billing, and delivery workflows. The remit is not product AI, but operational AI that links enterprise applications through model context protocols and agents, reflecting how mature SaaS companies are starting to treat automation as part of core systems architecture rather than a set of one-off scripts.
For a long-term SaaS career, the role builds durable leverage across the full revenue and operations stack. Work that spans NetSuite, Zuora, Jira, and cross functional stakeholders tends to translate well across SaaS companies because it touches the recurring revenue lifecycle, auditability, and the mechanics of scale. The emphasis on measurable impact and governance also aligns with how SaaS organizations operationalize AI responsibly in production environments.
This position will suit professionals who prefer systems thinking over feature delivery and who enjoy translating ambiguous business needs into reliable integrations and automation patterns. It is a strong match for architects or senior automation practitioners who want hands-on ownership while influencing standards, documentation, and adoption across multiple internal teams.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Role:
As the Enterprise Applications AI Architect, 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.
About the Team:
This role will report to the Enterprise AIT team, a group focused on driving the intelligent transformation of Gusto’s enterprise systems. The Enterprise AIT team is responsible for integrating AI, automation, and advanced analytics across our internal applications ecosystem to improve scalability, efficiency, and decision-making. Partnering closely with Finance, Business Ops, IT, and Security, the team enables Gusto’s enterprise systems to become smarter, more predictive, and more adaptive. This is a new role, designed to expand the team’s capacity to operationalize AI within enterprise workflows and support Gusto’s broader Enterprise Systems strategy.
Here’s what you’ll do day-to-day:
- 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 NetSuite, 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.
Here’s what we're looking for:
- 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, NetSuite, or similar, with a strong grasp of APIs, JSON, and RESTful service design.
- Hands-on knowledge of AI agent frameworks (for example LangChain, 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.
Our cash compensation amount for this role is targeted at $150,000-$165,000 /yr in Denver & most remote locations, and $185,000-$205,000 /yr for San Francisco, Seattle & New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.