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Gong.io

AI-driven revenue intelligence from conversations

Principal Product Marketing Manager

Product MarketingConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 8 years of B2B product marketing experience, including at least four years owning the full product marketing lifecycle for an AI platform, agentic infrastructure, or complex workflow product at an enterprise SaaS company, with demonstrated success marketing to technical buyers.
  • Working knowledge of agentic workflow concepts, including triggers, actions, plays, next-best-action, human-in-the-loop governance, Model Context Protocol integrations, and enterprise AI governance and data residency.
  • Exceptional written and verbal communication skills, including precision in writing, distilling architectural concepts into trustworthy narratives, and adapting messaging for business and technical audiences.
  • A bias toward evidence and action, including testing positioning with customers, validating it using win/loss data, and iterating based on what moves technical buyers.
  • Comfort operating in ambiguity and at pace, making sound decisions with incomplete information and adapting as the product and market evolve.
  • Experience marketing to Revenue Operations, Sales Operations, or revenue leadership personas, such as Chief Revenue Officers and Vice Presidents of Sales.
  • A track record of making complex, multi-layered systems coherent and credible to skeptical enterprise buyers, including explaining governance models, data permissioning, orchestration logic, or agent lifecycle management.
  • Prior experience working on a product that was actively defining or expanding a market category.
  • Experience with analyst relations, including presenting at briefings, shaping Gartner Magic Quadrant narratives, or contributing to Forrester Wave evaluations.
  • Comfort with quantitative analysis, including win/loss data, pipeline influence metrics, adoption curves, and consumption or credit pricing models.

Responsibilities

  • Own the technical buyer narrative by defining positioning and messaging that earns credibility with Chief Information Officers and Revenue Operations leaders evaluating enterprise AI infrastructure for revenue, and explain governance models, orchestration architecture, data permissioning, and agent lifecycle management.
  • Develop content, frameworks, and tools to help Chief Information Officers and Revenue Operations architects understand how Gong fits into their AI stack, covering data flows, governance controls, agent coordination, Model Context Protocol integrations, audit trails, and the Gong Revenue Graph's role as the grounding layer for reliable enterprise-scale autonomous execution.
  • Unify AI intelligence and execution into a single product story for technical buyers evaluating fragmented point solutions.
  • Make and defend recommendations about packaging and monetizing AI execution capabilities across the platform.
  • Bring structured buyer, competitive, and analyst insights into product planning; develop a point of view on how enterprise IT and revenue operations teams evaluate, adopt, and govern agentic AI; and advise the team on market evolution and enterprise platform decisions.
  • Partner with the broader product marketing team, product management, enablement, sales, post-sales, communications, and operations to drive launches from brief through execution.

About the Company

Gong.io

AI-driven revenue intelligence from conversations

Gong builds a revenue intelligence platform that analyzes every customer interaction to help sales teams win more deals. It records, transcribes, and analyzes calls, video meetings, emails, and chats to surface insights on deal health, sales tactics, and buyer/competitor trends. Using AI, it provides Deal Intelligence, People Intelligence, and Market Intelligence, flags risks, coaching opportunities, and next-best-action recommendations, and integrates with CRM, email, and collaboration tools. The goal is to turn conversations into data-driven actions to improve forecasting, coaching, and go-to-market decisions for mid-to-large enterprises.

Company size
1,001-5,000
Company stage
Series E
Total funding
$586M
Headquarters
San Francisco, CA
Founded
2015

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