GTM AI Operations Lead, Sales

What You'll Do

• Design, build, and maintain AI-powered automations across the sales motion — from opportunity hygiene and stage progression to forecasting inputs and rep nudges.
• Own the systems that keep data clean and trustworthy, so that downstream reporting and AI outputs are reliable by default.
• Partner with sales leadership to identify bottlenecks and ship automation that addresses root causes, not symptoms.
• Integrate and orchestrate the GTM tech stack — Salesforce, conversation intelligence (e.g., Gong)— with AI agents and workflows layered on top.
• Build internal tooling and lightweight applications that put AI insight directly in front of reps and managers inside their existing workflow.
• Establish guardrails for safe, governed AI use against revenue data — including permissioning, read/write boundaries, and human-in-the-loop checkpoints.
• Translate ambiguous "we should automate this" requests into scoped, measurable, and maintainable systems.

Required Skills & Experience

• 5-7 years in Revenue Operations, Sales Operations, GTM Systems, or a closely related function, with meaningful time supporting an enterprise sales motion.
• Hands-on Salesforce expertise — you can build, debug, and reason about data models, automation, and permissions, not just navigate the UI.
• Demonstrated experience designing and shipping automations, ideally including LLM- or AI-driven workflows (agents, prompt-based tooling, or AI features embedded in GTM systems).
• Strong analytical rigor: you can pull and interrogate pipeline data, pressure-test your own conclusions, and communicate findings crisply.
• Comfort building — Whether that’s no/low-code automation platforms, or API integrations — enough to prototype without waiting on engineering.
• A bias toward systems that are maintainable and trustworthy over clever-but-fragile.

Bonus Qualifications

• Experience standing up RevOps or GTM systems function from an early stage.
• Familiarity with conversation intelligence platforms and how to operationalize their data.
• Prior work integrating AI/LLM tooling with CRM data under read-only or tightly-scoped permissions.
• Background at a high-growth, AI-native, or developer-focused company.