Remote AI Review Lead - Operations & Policy QA

AuraOne, Inc.

United States

Remote

USD 62,000 - 96,000

Full time

14 days+

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Job summary

AuraOne, Inc. is seeking a Program Lead reviewer to evaluate AI outputs against program lead operations workflows and firm policies.

The role focuses on grading tone, escalation logic, and stakeholder fit using a structured rubric, while flagging policy-adherence gaps and operational risks. The contractor will document the right next steps to train the modeling team and adjudicate disputes using published playbooks, maintaining high inter-rater calibration scores.

Qualifications

  • Direct working experience in program lead operations on real teams for Program Lead work.
  • Comfort applying multi-page rubrics consistently across long batches.
  • Clear written reasoning that names the policy or workflow being applied.
  • Strong attention to detail and the ability to flag when a prompt itself is the problem.
  • Reliable async availability for at least 10 hours per week.

Responsibilities

  • Review AI outputs against current program lead specialist operations workflows, playbooks, and firm policy for Program Lead assignments.
  • Grade tone, escalation logic, and stakeholder fit on a structured rubric.
  • Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
  • Capture the right next step so the modeling team can train on it.
  • Adjudicate disputed treatments against published playbooks or firm guidance.
  • Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Operational review
Policy adherence
Workflow judgment
Stakeholder communication
Program Lead operations

Job description

AuraOne, Inc. is seeking a Program Lead reviewer to evaluate AI outputs against program lead operations workflows and firm policies.

The role focuses on grading tone, escalation logic, and stakeholder fit using a structured rubric, while flagging policy-adherence gaps and operational risks. The contractor will document the right next steps to train the modeling team and adjudicate disputes using published playbooks, maintaining high inter-rater calibration scores.

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