Inscribe AI
Account Executive
San Francisco · Mid
Sponsorship not specified$230k-$240kDetected 26 days ago
SalesAccount ManagementNegotiation
About the role
- As an Account Executive (our 2nd AE), you'll be at the forefront of Inscribe's growth, helping define how we sell as we scale.
- If you love complex, consultative sales and want to operate in a fast-moving, high-ownership environment alongside a sharp, low-ego team, then you'll thrive here.
Responsibilities
- Own the full sales cycle: prospecting, discovery, demo, negotiation, and close
- Build deep, trusted relationships with senior stakeholders across risk, fraud, and operations teams
- Drive net new business within a defined target account list
- Maintain a strong pipeline and deliver accurate weekly forecasts
- Partner cross-functionally with Product and Marketing to win deals
- At Inscribe, we are building a company and culture where everyone can produce their best work.
- Highly personable and able to quickly build trust with both customers and teammates
- In-Person Exercise with our Cofounders to evaluate your sales approach and relationship building skills (1 hour)
Skills
- Identify real customer pain points and position Inscribe's solutions in a clear, compelling way
- Represent Inscribe at industry events, conferences, and customer meetings
- Leverage AI tools and creative approaches to improve efficiency, outreach, and deal execution
Compensation
- The on-target earnings (OTE) for this role range from $230,000 to $240,000, with a competitive base salary and commission structure (typically a 50/50 split), plus uncapped commission and accelerators for top performance.
Benefits
- Here are a few of our benefits and perks:
- Competitive salary and meaningful equity
- Comprehensive healthcare
- Unlimited vacation policy
- 401(k) and pension plans
- Monthly wellness stipend
- Actual compensation will vary based on experience, skills, and internal equity considerations across the team.
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This listing is sourced directly from Inscribe AI's careers page and normalized into a canonical job model.