Principal Product Manager, AI

Job Description

Cisco's Enterprise AI Platform group is looking for a Principal Product Manager to help steer how the company's agentic AI tools take shape across its internal workforce. This isn't a role tucked into one feature area — it sits at the center of a team spanning engineering, UX, and product that's building the foundation other AI experiences at Cisco will run on. Whoever takes this on will be shaping how tens of thousands of employees interact with AI-driven automation every day.

What makes this role stand out is the scope: you're not optimizing a single tool, you're setting direction for a platform that other teams build against.

Key Responsibilities

• Shape the multi-quarter vision and roadmap for Cisco's enterprise AI/agentic platform, keeping it tied to both business priorities and what users actually need day to day.
• Own the requirements process end to end — running discovery with internal stakeholders, pulling insight out of focus groups, and turning fuzzy problems into clear, buildable Product Requirement Documents.
• Sit at the intersection of engineering, design, legal, and security teams, making sure new AI capabilities ship without compromising privacy or compliance standards.
• Push for automation that solves real friction points inside tools employees already live in — think Webex, Outlook, SharePoint, and Jira — rather than automation for its own sake.
• Run focus groups and structured feedback loops directly with users, then translate what you hear into prototype iterations that actually move the needle.
• Define what "success" looks like for each pilot — set the metrics up front, then use the resulting data to decide what scales and what gets reworked.

Requirements

• 10+ years in product management, with hands-on experience in an AI-adjacent domain — machine learning, NLP, or reinforcement learning.
• A track record of actually shipping products — not just pilots that stall, but things that went from concept through deployment inside a real enterprise environment.
• Comfort working alongside engineers on the technical side: APIs, system integrations, and how enterprise data architecture actually behaves in practice.
• Strong analytical instincts — the ability to take messy, conflicting feedback from multiple sources and boil it down into requirements engineering can actually build against.
• Working knowledge of privacy, security, and compliance expectations inside SaaS and enterprise software environments.

Preferred Qualifications

• Deeper specialization in generative AI or large-scale automation platforms, beyond general PM exposure to AI.
• Experience running workshops, structured user testing, and focus-group sessions as a core part of your product process.
• Comfortable operating with autonomy across a hybrid setup spanning San Jose, Research Triangle Park, or Seattle.
• Background building products where trust and privacy were part of the value proposition, not an afterthought.
• A blend of long-term strategic thinking and willingness to get hands-on with execution and metrics day to day.