Director, AI-Native Business Operations

This role leads the redesign of the core operating processes that run the CPO and product organization, rebuilding them as AI-native workflows operated by agents. The scope is the organization’s own operating model: budgeting and requisition management, resource and funding allocation, planning cycles, and the executive business reviews that govern how the organization plans, spends, staffs, and decides. These processes consume significant leadership time today and run largely on spreadsheets, email, and meetings. The role is accountable for re-architecting them and delivering the agents that operate them in production.

This is a hands-on role. The person in it personally designs and builds the agents and integrations that run these processes, selects the appropriate tools for each problem, and adapts across changing tooling, models, data sources, and systems of record. Familiarity with the team’s preferred tools, Cursor and Claude Code, is expected, alongside the range to work in whatever technology stack a given process requires.

The role reports directly to the VP, Analytics Growth and AI Native Engineering. It leads a cross-functional team that includes engineers who build the agents, operations managers who run the redesigned processes day to day with those agents in the loop, and program management responsible for landing the new operating model across the organization. It partners closely with Finance, the People function, platform engineering, security, and compliance to ensure the processes it delivers are accurate, auditable, and scalable.

• Lead the redesign of the organization’s core operating processes, including budgeting, requisition and headcount management, resource and funding allocation, planning cycles, and executive business reviews, converting them into AI-native workflows operated by agents.
• Design, build, and deploy the agents and integrations that run these processes, working hands-on across the appropriate tools, models, data sources, and systems of record, and evolving the technology stack as requirements and the tooling landscape change.
• Re-architect budget and headcount management, including capacity for senior hiring, reallocation of unfilled roles, and modeling of the funding levers that support AI investment.
• Re-architect the planning process, including the transition toward a continuous planning model, so that capacity allocation, prioritization, and sequencing operate on trusted, instrumented data rather than manual reconciliation.
• Standardize the executive business review format across business units, automating preparation, exception reporting, and follow-up.
• Establish trusted tracking, reporting, and instrumentation for the cost, capacity, and portfolio data these processes depend on, ensuring a single source of truth across the operating model.
• Define the governance for each workflow, including audit trails, cost controls, access scope, escalation paths, and the criteria for expanding agent authority, in partnership with Finance, security, legal, and compliance.
• Partner with senior operating stakeholders to define operational requirements, deliver against them, and demonstrate measurable impact in leadership time returned, cycle time reduced, and decision quality improved.
• Transition mature processes to platform engineering, with the integration patterns, runbooks, and documentation required to operate them at NetApp scale.
• Build and lead the team that delivers the operating model, including engineers who build the agents, operations managers who run the processes day to day, and program management responsible for adoption and change across business units. Set direction, hire and develop the team, and hold accountability for delivery and impact.