Account Executive

Endgame

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profile Job Location:

San Francisco, CA - USA

profile Monthly Salary: $ 225 - 275
Posted on: 8 days ago
Vacancies: 1 Vacancy

Job Summary

About Endgame

Endgame is building the context engine for go-to-market. The bet underneath the company: the hard part of applied AI isnt the model its getting the right context to it. Real enterprise data is messy. Duplicated contacts across seven systems deals referenced by nickname in Slack methodology that lives in someones head. Models cant reason their way out of that. You have to do the work upstream.

So thats what we do. Entity resolution across CRM and conversational data fact extraction with provenance retrieval that respects permissions and recency methodology encoded as first-class structure. The output: a layer that powers both day-to-day GTM work and the agents teams build on top of it agents that work in production not just demos. Companies like Monte Carlo BetterUp Braze Hex and Vistra run their revenue motion on it.

Were a small technical team solving specific unsolved problems at the boundary of data engineering and applied AI. If thats the work you want to be doing wed like to meet you.


Your Mission

Were looking for an Account Executive whos excited to sell a complex technical platform to enterprise GTM teams. Youll partner with a Forward Deployed Engineer on every account working closely with prospects to help them transform to AI-native GTM organizations and own the customer lifecycle: through deployment renewal and expansion.


Your Responsibilities

  • Build pipeline Self-source opportunities through outbound and your network.

  • Run consultative discovery Uncover how the prospect is already trying to build with AI for GTM what theyve tried and where theyre stuck.

  • Engage executives top-down work with our CEO to get in front of the Economic Buyer early and keep that thread alive through close.

  • Multi-thread the buying committee Engage business champions technical champions and economic buyers in parallel; pull the right people out of Slack threads and calendar invites not just the CRM contact list.

  • Own MEDDPICC discipline and pipeline hygiene Qualify thoughtfully and disqualify early.

  • Own the customer post-close Partner with your FDE to drive adoption expansion and renewal. The relationship doesnt transfer; it deepens.


Our Ideal Candidate

  • Youve closed complex enterprise software deals 5 years selling at $500K ACV with multi-stakeholder buying committees and multi-month cycles. Complex SaaS infrastructure or AI/data platforms preferred.

  • Youre conversant on AI and data architecture you can hold a credible technical conversation with a CIO CTO or Head of GTM Engineering without needing an SE in the room.

  • You build executive relationships youve gotten Economic Buyers (CROs CEOs CIOs) into the room and kept them engaged through close.

  • You qualify well you know the prospect who isnt ready and youd rather walk away or reset scope than burn quarters chasing.

  • You hit the number and you can name how youve ramped quickly into new motions ICPs and categories before.

  • Comfortable in a fast-paced startup environment adapting quickly and collaborating across diverse teams.

Benefits

  • Competitive compensation and equity

  • 401k health dental and vision insurance

  • Flexible time off

  • Paid parental leave

  • Education stipend

The qualifications listed in our job descriptions are meant as guidelines not strict requirements. You dont need to meet every qualification to apply if you believe your skills and experience make you a strong candidate we want to hear from you. Apply directly or reach out to us at .

The qualifications listed in our job descriptions are meant as guidelines not strict requirements. You dont need to meet every qualification to applyif you believe your skills and experience make you a strong candidate we want to hear from you! Apply directly or reach out to us at


Required Experience:

IC

About Endgame Endgame is building the context engine for go-to-market. The bet underneath the company: the hard part of applied AI isnt the model its getting the right context to it. Real enterprise data is messy. Duplicated contacts across seven systems deals referenced by nickname in Slack method...
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