Join Rippling as a Staff Software Engineer to pioneer a new product category focused on AI Governance. This role is critical in shaping how companies manage and secure their AI usage. You will build systems that ensure AI applications are attributable, policy-compliant, and budget-conscious.

This is a unique opportunity to tackle high-ambiguity, high-impact challenges. You will develop foundational platform technology at the intersection of identity, access control, and data protection, while staying connected to evolving customer needs in the rapidly advancing AI landscape.

Lead the technical architecture for key AI governance systems, including access control for MCP, model gateway policies, and runtime authorization. Design robust distributed systems that enforce policies efficiently without introducing latency or fragility. Develop identity-aware controls that link AI usage to Rippling's organizational data, roles, and permissions.

Take ownership of ambiguous product and technical challenges related to shadow AI detection, agent permissions, tool access, spend attribution, and data protection. Collaborate with Product, Security, Legal, IT, and Engineering leaders to establish durable platform capabilities. Define the technical direction for a new team, focusing on architecture, design standards, reliability, and system boundaries. Mentor senior engineers and elevate the engineering bar for critical, secure, and observable systems.

Requires 8+ years of professional software engineering experience with demonstrated technical leadership and organizational impact. Deep expertise in backend and distributed systems design, with a focus on services featuring clear ownership, strong reliability, and well-defined interfaces.

Possess high agency and a bias for action, capable of translating ambiguous product ideas into focused launches, rapid feedback loops, and stable technical foundations. Demonstrate an AI-native engineering mindset, leveraging AI tools effectively while understanding where human judgment is crucial for correctness, security, and architecture. Exhibit strong security and systems judgment, particularly concerning authorization, identity, data movement, audit logs, or policy enforcement.

Cultivate product sense for enterprise software, prioritizing customer-visible impact and operational simplicity. Communicate effectively with both technical and non-technical stakeholders, skillfully navigating trade-offs between security, usability, and speed. While familiarity with AI infrastructure, LLM gateways, MCP, developer tools, identity systems, or data protection is advantageous, it is not strictly required.