Responsibilities

• Own the technical buyer narrative — define positioning and messaging that earns credibility with CIOs and RevOps leaders evaluating enterprise AI infrastructure for revenue. Go beyond outcomes: make governance models, orchestration architecture, data permissioning, and agent lifecycle management feel purpose-built and immediately trustworthy.
• Build the infrastructure conversation — develop the content, frameworks, and tools that help CIOs and RevOps architects understand how Gong fits into their AI stack. This means data flows, governance controls, agent coordination, MCP integrations, audit trails, and the role of the Gong Revenue Graph as the grounding layer that makes autonomous execution reliable at enterprise scale.
• Unify AI and execution into a single story — intelligence and execution are one product. Your job is to make the integrated picture feel inevitable to a technical buyer who has spent the past 18 months evaluating fragmented point solutions and wondering why none of them hold up in production.
• Take a portfolio view — make and defend recommendations about how AI execution capabilities are packaged and monetized across the platform.
• Shape product and GTM strategy — bring structured buyer, competitive, and analyst insights into product planning; develop a deep POV on how enterprise IT and revenue operations teams evaluate, adopt, and govern agentic AI; be the team’s expert on how this market is evolving and how enterprises are making platform decisions.
• Drive high-impact launches — partner with the broader PMM team, PM, Enablement, sales, post-sales, comms, and ops to drive launches from brief to execution.