Senior Product Manager - Mesh

ZoomInfo Careers Accelerate

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You'll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won't just contribute. You'll make things happenfast.

The Opportunity

ZoomInfo built an enterprise AI platform that 2,700+ employees use every day not because they were told to, but because it produces work they can't get anywhere else. Mesh is our internal-turned-commercial AI platform: conversational AI, an agent builder with 6,600+ agents deployed, 550+ no-code microapps, and integrations across 35+ enterprise tools.

This role owns the core product experience the chat interface, the agent platform, the microapps SDK, the tooling layer, and the dashboards that make the platform usable, powerful, and indispensable. You're not building AI features on top of an existing product. You're building the product that IS the AI platform.

Every department at ZoomInfo uses what you build. Sales uses it to prep for demos and generate follow-up emails. Customer Success uses it for account plans and renewal analysis. Engineering uses it for code review and incident investigation. RevOps uses it to automate workflows that used to require entire teams. When 10 departments across a 3,200-person company depend on your product daily, the decisions you make what to build, what to improve, what to say no to have immediate, visible impact.

What You'll Do

Own the Core Product Experience. You own chat, agents, tools, and dashboards the surfaces where 2,700+ users interact with the platform every day. Define what gets built, how it works, and why it matters. Prioritize ruthlessly across a product with enormous surface area, balancing power-user depth with new-user accessibility. Ship improvements that users notice on Monday morning.

Drive Agent Platform Evolution. 6,600+ agents have been built on your platform. Your job is to make the next 6,600 easier, faster, and more powerful. Own the agent creation experience, the sharing and discovery model, the scheduling system, and the analytics that help builders understand what's working. Understand how a sales rep in their first week and a principal engineer with 15 years of experience both need to succeed with the same tool.

Shape the Dashboard and Analytics Layer. Users need to understand what's happening their conversations, their agents' performance, their team's adoption, their cost. Own the dashboards and analytics surfaces that make the platform transparent and manageable. Define the metrics that matter for individual users, team leads, and platform administrators.

Manage the Tooling Ecosystem. Agents are only as powerful as the tools they can invoke. Own the tooling layer how tools are surfaced, configured, and composed within the chat and agent experiences. Partner with integration teams to ensure new MCP connections translate into capabilities users can actually leverage without reading documentation.

Be the Voice of 10 Departments. Your users span Sales, CS, Marketing, Engineering, RevOps, Data, Finance, Legal, HR, and Customer Experience. Each has different workflows, different expectations, and different definitions of "done." Build feedback loops that surface real needs, not just loud requests. Spend time with users. Watch them work. Understand the difference between what they ask for and what they actually need.

What You'll Bring

• 6 years of product management or adjacent strategy experience, with at least 2 year working on AI/ML products, and 1 year working on internal platform products
• Experience owning a product portfolio with real daily users you've shipped improvements to people who depend on your product and tell you when it breaks and you are used to working with teams of engineers.
• Familiarity with AI/LLM products you understand the basics of how conversational AI, agents, and tool-calling work, even if you're not writing the models yourself
• Comfort with data you can SQL, read a dashboard, run a user experience test, and use metrics to make prioritization decisions rather than relying on intuition alone
• Track record of working cross-functionally you've navigated competing stakeholder needs and made prioritization calls that not everyone agreed with
• Experience with enterprise software or internal tools

Who You Are

User-Obsessed, Not Feature-Obsessed. You start with the problem, not the solution. When a user says "I need a button that does X," you ask why three times before opening a spec. You've learned that the best product decisions often involve not building something and you can explain that decision clearly to stakeholders who disagree.

Comfortable with Ambiguity. The AI landscape changes weekly. User needs evolve as they discover what's possible. You don't need a perfectly scoped roadmap to make progress. You can hold a long-term vision while making short-term calls with incomplete information. You update your plan when the evidence changes, not when it's convenient.

Technically Curious, Not Technically Intimidated. You don't need to train models or write production code. But you need to understand how agents work well enough to have credible conversations with engineers, identify when a technical constraint is real versus assumed, and prototype ideas when words aren't enough. You read release notes for fun. You've tried building something with an LLM API at least once.

Cross-Functional by Default. Your product touches every department. You thrive in environments where you're constantly context-switching between a sales leader who needs better demo prep and an engineer who needs better error handling. You build relationships through reliability people trust you because you follow through, not because you tell them what they want to hear.

High Standards, Low Ego. You care deeply about craft the copy in an empty state, the load time of a dashboard, the default sort order in a list. But you also know when good enough is good enough. You take feedback well, give it directly, and don't confuse your opinion with the user's reality.

Bias Toward Shipping. You'd rather ship something imperfect on Tuesday and iterate than debate the perfect solution until Friday. You understand that in a fast-moving AI product, learning from real usage beats planning in a vacuum every time.