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Mercor
Mercor

Enterprise AI Lead

RoleOperations
LevelLead
LocationSan Francisco, United States
WorkOn-site
TypeFull-time
Posted1 month ago
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ABOUT MERCOR

Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.

Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our new San Francisco headquarters.

About the Role:

As an Enterprise AI Lead, you will work directly with our VP of Enterprise AI to build and scale Mercor's enterprise business. This is a senior, high-ownership role that sits at the intersection of commercial and operational work, designed for someone who moves fast, communicates well, and has a genuine interest in what AI can do for large organizations.

Responsibilities:

  • Own relationships with enterprise customers from initial engagement through renewal and expansion

  • Build and execute on commercial strategy, including pipeline development, proposals, and negotiations

  • Lead cross-functional initiatives across sales, product, and operations

  • Drive internal planning and operating cadence for the Enterprise team

  • Develop and deliver materials for executive-level audiences, including readouts, business cases, and strategic analyses

  • Identify and pursue new business opportunities in partnership with the VP of Enterprise AI

Requirements:

  • 5 or more years of experience in a client-facing role, such as management consulting, enterprise sales, private equity, or a GTM or operations role at a technology company

  • Strong written and verbal communication skills with experience presenting to senior stakeholders

  • Demonstrated ability to manage complex workstreams independently and deliver results

  • Genuine curiosity about AI and how it is reshaping enterprise organizations

  • High agency and comfort operating in a fast-moving, ambiguous environment

Nice to Haves:

  • Experience in strategy consulting at a top-tier firm, particularly in technology sectors

  • Prior exposure to enterprise AI or SaaS commercial motions

  • Background in venture capital or private equity with client-facing responsibilities

Compensation and Benefits:

  • Competitive salary and bonus earning potential + meaningful equity (aligned with a venture-backed, rapidly scaling AI company)

  • Medical, dental, and vision coverage

  • 401(k)

  • Monthly meal stipend

  • Excellent in-office culture

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About Mercor

Mercor

Mercor

Seed

Mercor is an AI-powered platform that connects companies with vetted software engineers and technical talent through automated screening and matching processes.

1-50

Employees

San Francisco

Headquarters

Reviews

10 reviews

4.0

10 reviews

Work-life balance

3.2

Compensation

3.8

Culture

4.3

Career

3.5

Management

4.2

72%

Recommend to a friend

Pros

Supportive and approachable management

Great team culture and collaborative environment

Good benefits and flexible work options

Cons

Heavy workload and frequent overtime

Communication issues and miscommunication

Non-competitive pay and limited career progression

Salary Ranges

6 data points

Mid/L4

Mid/L4 · Machine Learning Engineer

1 reports

$210,126

total per year

Base

$161,637

Stock

-

Bonus

-

$210,126

$210,126

Interview experience

3 interviews

Difficulty

3.0

/ 5

Offer rate

67%

Experience

Positive 0%

Neutral 67%

Negative 33%

Interview process

1

Application Review

2

AI Interview Screen

3

Technical Assessment

4

Final Review

5

Offer

Common questions

Domain Expertise

Behavioral/STAR

Industry Knowledge

Leadership Experience

Problem Solving