Enterprise AI Associate

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. 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 San Francisco, NYC, or London offices. About the Role As an Enterprise AI Associate, you'll work at the intersection of customer engagement, product management, and go-to-market operations — helping Mercor's largest enterprise customers successfully deploy and scale AI solutions. This role is built for someone with a structured, analytical mindset who thrives on high agency, moving quickly, and taking ownership of ambiguous problem statements. You'll be embedded in active customer engagements, working alongside senior Enterprise leads in conversations with senior stakeholders about their top organizational AI priorities and pain points, and translating those needs into engagement delivery. You will play a critical part in shaping our offerings by supporting our go-to-market motion, brand positioning, and relaying customer feedback to engineering. What You'll Do Support the end-to-end delivery of enterprise AI engagements - scoping workstreams, tracking milestones, and coordinating across internal and client-side stakeholders Join client meetings to document AI pain points, synthesize top organizational priorities, and identify specific workflows where Mercor can drive value Translate qualitative client feedback and edge cases into structured execution plans, working directly with engineering teams to shape new AI agent capabilities Step into ambiguous problem spaces - scope unowned internal initiatives, define clear goals, and drive projects forward when there is no established playbook Refine go-to-market messaging and sales collateral - converting real-world customer interactions into updated pitch decks, company blurbs, and brand positioning Contribute to internal process improvements - building playbooks, templates, and frameworks that make the team more effective at scale Stay current on trends in frontier AI, enterprise AI deployment, and data operations to bring an informed perspective to client conversations What We're Looking For 1–3 years of experience in management consulting, operations, strategy, product management, or a similarly structured analytical environment Strong ability to break down complex problems, structure work plans, and communicate findings clearly to diverse audiences Excellent operational instincts - you track details without losing sight of the bigger picture Comfortable navigating ambiguity and proposing solutions when there's no clear playbook Genuine intellectual curiosity about AI - you don't need to be an engineer, but you should want to understand how these systems work and why they matter Collaborative by nature, with the ability to build trust quickly with both clients and internal teammates Bonus: prior exposure to AI, data operations, or technology-adjacent work How You Work High-agency operator: you proactively insert yourself into undefined challenges Structured thinker: you approach messy problems with frameworks and clear hypotheses Strong communicator: you write and speak with precision, adjusting your style for technical and non-technical audiences Delivery-oriented: you take ownership of workstreams and see them through to completion Curious and adaptable: you learn quickly and bring energy to new domains 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

{
  "content_hash": "f44ac98b65306e2cf10d5f907b68d99575dec304e4ebdb2049a2f54c2eba25b2",
  "source_hash": "a88db395d0bba2f475717a6399a68ad0860ec9aebb8a7d3b90053a692104c7e5",
  "last_changed_at": "2026-05-29T06:25:55.233Z",
  "active_status": "active"
}

{
  "language": "en",
  "location": {
    "raw": "San Francisco",
    "city": "San Francisco",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.75
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-06T09:21:37.601Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "San Francisco",
      "city": "San Francisco",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.75
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": null,
  "workplace_type": "on_site",
  "salary_currency": null
}

{}

{
  "id": "50a58426-2e97-43a5-99b1-d0d9cdc88100",
  "team": "Enterprise",
  "title": "Enterprise AI Associate",
  "jobUrl": "https://jobs.ashbyhq.com/mercor/50a58426-2e97-43a5-99b1-d0d9cdc88100",
  "address": null,
  "applyUrl": "https://jobs.ashbyhq.com/mercor/50a58426-2e97-43a5-99b1-d0d9cdc88100/application",
  "isListed": true,
  "isRemote": false,
  "location": "San Francisco",
  "updatedAt": null,
  "apiVersion": "ashby-non-user-graphql-v1",
  "department": "Enterprise",
  "publishedAt": null,
  "workplaceType": "OnSite",
  "employmentType": "FullTime",
  "secondaryLocations": [
    {
      "location": "New York City"
    }
  ]
}