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Head of Revenue

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Base
Full Time position
Listed on 2026-09-13
Job specializations:
  • Sales
    Customer Success Management, Account Manager, Client Relationship Management, B2B Sales
Salary/Wage Range or Industry Benchmark: 250000 - 450000 USD Yearly USD 250000.00 450000.00 YEAR
Job Description & How to Apply Below

A hands-on commercial leader to build, carry, and scale new business, renewals, and expansion.
About Base

Base is building the AI Customer Growth Platform for modern B2B companies. We help teams orchestrate customer engagement across the post-sale lifecycle - from onboarding and adoption to expansion, advocacy, and retention - through one unified platform.

We are a growing startup selling to sophisticated enterprise Marketing, Customer Success, and GTM organizations that are rethinking how they operate in the age of AI. We are doing the same internally.

The role

We are looking for a hands-on Head of Revenue to own and rebuild an AI-first commercial revenue engine. The remit spans new business and the commercial side of the customer lifecycle: upsell, cross-sell, expansion and renewals.

This is a build-and-carry role, not a traditional CRO role. You will lead Sales and Account Management, personally run strategic opportunities, coach the team in live deals, and create a more repeatable and productive revenue motion. You will work directly with the CEO and help shape the engine Base will run on for the next several years.

A separate Customer Success organization owns onboarding, adoption, value realization, customer health, and support. Your team owns pricing, negotiation, contracts, renewals, and closing expansion. The partnership between Revenue and Customer Success is central to the role;
Customer Success does not report to the Head of Revenue.

What you'll own
  • Revenue performance across new ARR, renewal ARR, upsell, cross-sell, expansion, and net revenue retention.
  • A trusted forecast across new business and the installed base.
  • The Sales and Account Management teams, including coaching, operating cadence, role clarity, hiring, and development.
  • A repeatable AI-first enterprise sales motion: ICP, pipeline creation, qualification, discovery, multi-persona selling, demos, proposals, negotiation, and close.
  • A systematic AI-first renewal and expansion motion, including account planning, triggers, ownership, timing, pricing, commercial conversations, and contracting.
  • A small portfolio of strategic new-business and existing-customer opportunities that you personally lead from discovery through close.
  • Revenue productivity, compensation design, tooling, automation, data quality, and operating discipline.
  • A strong feedback loop with Marketing on pipeline and positioning, and with Product and Engineering on won/lost insights, commercial friction, and market demand.
  • The redesign of sales and post-sale revenue with AI-first operational lens.
How Revenue partners with Customer Success

Revenue and Customer Success will operate as peer organizations with shared visibility and clear ownership. Customer Success owns customer outcomes and the day-to-day value relationship;
Revenue owns every commercial close. Together, the teams will maintain joint account plans, identify risk early, and translate customer health and usage signals into the right renewal or expansion action.

  • Customer Success owns onboarding, adoption, time-to-value, customer health, and support.
  • Revenue owns pricing, proposals, negotiation, contracts, renewals, upsell, cross-sell, and expansion close.
  • Customer Success surfaces and helps qualify risk and growth signals;
    Revenue turns qualified commercial opportunities into closed business.
  • Both teams protect revenue quality: selling the right solution, expanding at the right time, and building durable customer relationships.
Build an AI-native revenue organization

A central part of the mandate is redesigning how commercial work gets done - not simply adding AI tools to an old operating model. You will determine where AI and automation can improve or replace work across research, prospecting, preparation,…

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