Gamma

Gamma

Senior Commercial Counsel

San Francisco · Senior · Full-time

Sponsorship not specified$180k-$260kDetected 132 days ago
Machine LearningComplianceSalesCommunication

About the role

  • Gamma has over 70 million users, is profitable with $100M+ ARR, and is making a major push into B2B enterprise sales.
  • The volume and complexity of our legal work is growing fast.
  • We need someone who can keep pace, exercise sharp judgment, and move work forward without a team of specialists behind them.

Responsibilities

  • Advise Product and Engineering on privacy-by-design, AI compliance (including EU AI Act readiness), and data handling practices
  • Help build scalable legal processes, playbooks, and templates to support Gamma's growing B2B motion
  • you'll run enterprise deal cycles end to end, help build out our privacy compliance program, and advise cross-functional teams on everything from data handling to AI regulation.

Nice to have

  • Run enterprise deal cycles alongside the GTM, including negotiations with sophisticated legal teams at large counterparties
  • Evolve Gamma's data privacy compliance program
  • JD and active bar membership (California preferred), with 4-7 years of legal experience including meaningful time at a major law firm and at least 2-3 years in-house at a SaaS or technology company
  • Comfort operating across a wide surface area with limited resources.
  • You don't need a team of specialists behind you to move work forward
  • Sharp judgment on when to protect and when to clear the path, with clear, direct communication that works whether you're explaining a redline to a sales rep or a privacy obligation to an engineer

Compensation

  • The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $260K plus benefits & equity.

Company info

  • Deep experience negotiating SaaS commercial agreements with enterprise customers

This listing is sourced directly from Gamma's careers page and normalized into a canonical job model.