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LLM Power User - MCP Specialist

Job in New York, New York County, New York, 10261, USA
Listing for: Mercor
Full Time position
Listed on 2026-08-22
Job specializations:
  • Business
    AI Evaluation
Salary/Wage Range or Industry Benchmark: 60000 - 90000 USD Yearly USD 60000.00 90000.00 YEAR
Job Description & How to Apply Below
Location: New York

About the Opportunity

A leading AI research organization is seeking advanced LLM power users with strong experience using MCP and (more importantly) plugins/connectors for real-world personal life tasks.

This project focuses on evaluating how well AI systems handle personalized, multi-step life tasks that require context, judgment, planning, and use of connected tools such as Google Drive, Expedia, Notion, and other plugins/connectors.

This role is ideal for people who use AI heavily in their personal lives and can do a better job replicating what AI could do if it weren’t available

What You’ll Do

You will help evaluate AI systems on complex personal workflows, including tasks across:

  • Personal health

  • Travel

  • Activity planning, including food and dining

  • Services, such as home repair

  • Career search

  • Other life organization workflows

Responsibilities may include:

  • Creating realistic prompts for complex personal-life tasks

  • Executing tasks and actions while recording your screen (required)

  • Using your personal plugins/connectors while you complete actions

  • Writing clear explanations of AI successes and failures

  • Judging whether AI outputs are practical, personalized, and well-reasoned

  • Identifying where models miss context, overreach, fail to use tools correctly, or produce unrealistic results

  • Creating and applying detailed rubrics to assess model performance

Who We’re Looking For

Strong candidates will have:

  • US-based only

  • Strong MCP experience and plug in / connector usage

  • Experience using LLM plugins/connectors such as Google Drive, Expedia, Notion, and similar tools, multiple times a week

  • Heavy personal usage of LLM products

  • An active, rich LLM account with regular usage and approximately 6+ months of history

  • Willingness to sign a data-share consent form via Docu Sign

  • Experience using AI for multi-step planning, research, decision-making, or personal workflows

  • Strong written judgment and attention to detail

  • Ability to explain what makes an AI output good, bad, incomplete, unsafe, or unrealistic

  • Experience writing and evaluating against rubrics

Extensive rubric experience is especially valuable, including 100+ hours on prior rubric projects involving rubric design, evaluation, and quality assessment.

Ideal Candidate Profile

The strongest candidates are LLM power users who are already using plug‑in tools in their personal lives for high-context tasks such as trip planning, health research, home services, food and dining decisions, career planning, personal organization, or similar workflows.

Candidates who want to be more competitive for this and future opportunities are encouraged to proactively spend time learning MCP and using LLM plugins/connectors before applying.

Why This Work Matters

LLMs are quickly becoming personal assistants for everyday decisions, but truly useful AI needs to do more than produce generic advice. It needs to understand context, preferences, constraints, tradeoffs, and what success looks like in real life.

Your evaluations will help improve how AI systems support people with practical, high-context tasks across food, health, travel, productivity, careers, and life organization. This work directly contributes to making AI assistants more personalized, trustworthy, and useful for real-world personal workflows.

Engagement Details
  • Expected commitment: 20+ hours/week

  • Ramp-up: 1–2 days required

  • Turnaround expectation:
    Ability to complete tasks within 24 hours

  • Equipment:
    Desktop or laptop required;
    Chromebooks are not supported

  • Experts added to the project will begin in a trial period to assess project fit, quality, and consistency before being considered for ongoing tasking.

  • Please note:

    This project is still in its early stages, so there may be an initial delay before tasking begins.

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