Product Manager, Agentic Operations

About the role

This role partners with leaders across NetApp to apply AI-native ways of working to high-value processes inside the company. The work is hands-on and engagement-based: partner with a team to understand how their work runs today, design a future state where AI agents accelerate and augment the work, build and pilot the solution, and partner with the team to make the new way of working durable. The role applies product management discipline — diagnosis, prioritization, specification, iteration, and measurement — to the design and delivery of agent-driven workflows. The unit of delivery is a working solution adopted by a partner team, not a roadmap or a recommendation. The role sits within the Agentic Product Management team under the VP, Analytics Growth and AI Native Engineering, and reports to the Director, Agentic Product Management. The team works in close partnership with platform engineering, security, and compliance to ensure that the workflows we ship are safe, auditable, and scalable. A few principles shape how the team approaches its work: We start from outcomes, not from tasks. The first question on any engagement is what the process is for and what good looks like, not how to automate the current steps. We deliver working solutions, not recommendations. Every engagement ends with a prototype that real users can run. We design with audit trails. Every workflow is inspectable: which agent did what, against what input, with what reasoning. We expand trust deliberately. Agents start with bounded authority, and authority grows as evidence accumulates.

Responsibilities

• Partner with the team that owns the process. Build the relationship with the leader and the operators who do the work today.
• Conduct working sessions to understand inputs, outputs, decision points, tools, cycle time, and the moments where the work most often gets stuck.
• Produce a current-state view that the partner team agrees is accurate.
• Define the outcome. Work with the partner-team leader to articulate what the process is actually trying to achieve and what good would look like.
• Identify which steps require human judgment, which serve regulatory or customer-facing purposes, and which exist because of tooling constraints.
• Quantify the prize: hours returned, cycle time reduced, quality improved, or capacity unlocked.
• Design the future state. Produce a future-state design that