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Enterprise Sales Domain Expert

$60–$90/h

United States

Catalogue update: this role is no longer listed in the current Mercor catalogue. Browse current AI Training opportunities.

About the role

Use enterprise selling experience to teach AI what effective sales work looks like. The assignment involves reviewing complete workflows and producing expert reference examples.

Skills and focus areas

Sales · Teaching · Auditing · CRM · Salesforce · Google Workspace

What you will do

  • Assess prospecting, pipeline, CRM and customer-communication workflows.
  • Complete realistic sales tasks in test environments.
  • Produce credible pitches and decision materials.
  • Improve scoring criteria so they reflect practical selling judgment.

Experience and requirements

  • Around ten years of hands-on enterprise sales experience.
  • A demonstrable record of quota performance.
  • Strong understanding of the full sales cycle and the ability to explain decisions.

Working arrangements

  • Full-time W-2 role through Cincinnatus LLC, working remotely within the US.

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Future of work · September 2026

How big is the remote / hybrid opportunity?

Remote work is already huge — but the bigger story may be the hundreds of millions of jobs that could still move beyond geography.

Global remote and hybrid work opportunity infographic

Remote work already connects millions of people with companies they would never have been able to work for a decade ago. But compared with the size of the global labour market, it may still be early.

The interesting number is not only how many people work remotely today — it is how many roles could plausibly become remote or hybrid next.

The chart above starts with roughly 3.3 billion people employed worldwide. Around 300 million jobs are already remote or hybrid, while an additional pool of roughly 250 million roles could potentially move in that direction as technology, workflows and company culture continue to change.

Skills are becoming more portable

This matters because more work can increasingly be matched to expertise rather than location. AI training and evaluation are a good example: companies need lawyers, engineers, designers, editors, researchers, finance professionals and many other specialists to help improve AI systems.

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