Senior Product Manager

Zoom is a company focused on building the best collaboration platform for the enterprise, and they are seeking a Senior Product Manager to own Common Room's integrations and data-sync surface. The role involves partnering with customers and teams to ensure data reliability and manage product areas that enhance customer trust in their GTM data.

Responsibilities:

• Defining the integrations and platform strategy and roadmap. This is the surface area that determines whether customers trust our data enough to run their GTM on it
• Making reliability a product outcome: uptime, data freshness, and accuracy customers never have to think about — and fast, legible triage when something does break
• Shipping AI agent workflows and APIs that move real GTM work across customer systems end-to-end: enrichment, sync, signal-to-action — not demos, production
• Owning a small set of customer relationships directly, and turn what you learn into product bets the whole company can rally behind. Especially where integrations make or break a renewal
• Partnering with engineering and design to make complex capabilities seem simple. Self-serve integration setup a non-technical RevOps lead can actually configure, sync behavior a data team can actually trust
• Owning the work through migrations, deprecations, enablement, and the Sales and CS feedback loop that turns features into retained revenue
• Raising the bar on product craft across the team — through the work you ship and the way you operate

Requirements:

• Have 6+ years in product management. (At least one tour owning integrations, data sync, or a platform/API surface for B2B SaaS — CRM (Salesforce, HubSpot), sales-engagement platforms (Outreach, Salesloft, Apollo), webhooks)
• Have PM-level fluency with the integration primitives. (OAuth, webhooks, rate limits, and data mapping/object sync) Enough to make the calls and earn engineering's trust without writing the API code yourself
• Have a track record of owning reliability as a product outcome, rather than treating it as engineering's problem. (Uptime, freshness, accuracy, error rates, incident triage)
• Demonstrate real fluency with AI products: you've shipped LLM- or agent-powered features in production. You have opinions about evals and agent design, and you know where the technology genuinely helps versus where it's marketing
• Have a first-principles take on what GTM should look like in an AI-agent world. As well as the systems thinking to assess how one decision ripples across data, identity, and downstream syncs and agents
• Be comfortable with being the direct responsible individual for customer relationships. Running discovery, sitting in on calls, and translating into specs — and calm as the escalation point when an integration breaks