Legal Expert (Antitrust & Competition Law)

AuraOne Human Data

United States

Remote

USD 55,000 - 110,000

Part time

14 days+

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Job summary

AuraOne, Inc. is seeking a Legal Expert (Antitrust & Competition Law) for a remote review track focused on evaluating AI outputs in legal review workflows.

Reviewers assess citation accuracy, statutory reasoning, and policy adherence, flag risks, and document corrected analyses to train the modeling team. The role emphasizes high-precision legal judgment, with an emphasis on citation checks, jurisdictional accuracy, and adherence to firm policy.

Qualifications

  • Active or recent qualification in legal review or an adjacent practice for Legal Expert (Antitrust & Competition Law) work.
  • Hands-on experience drafting, reviewing, or advising on real matters.
  • Clear written reasoning that cites authority and names the rule being applied.
  • Reliable async availability for at least 10 hours per week.

Responsibilities

  • Review AI outputs against current legal review statutes, case law, or policy for Legal Expert (Antitrust & Competition Law) assignments.
  • Verify citations, jurisdictions, and dates against authoritative sources.
  • Flag risky reasoning, missed exceptions, and policy-adherence gaps with severity tags.
  • Capture the corrected analysis or memo paragraph so the modeling team can train on it.
  • Adjudicate disputed treatments against published authority or firm policy.
  • Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Legal research
Citation review
Statutory analysis
Policy reasoning
Legal review
Legal

Job description

Legal Expert (Antitrust & Competition Law) is a remote review track for evaluating AI outputs in legal review workflows. Reviewers grade citation accuracy, statutory reasoning, and policy adherence; flag risk; and document the corrected analysis so the modeling team can train on it.

Why this role matters

Legal review content is judged on precision. AuraOne uses qualified legal and policy reviewers to grade AI outputs the way a senior associate would — with citations, severity tags, and the corrected reasoning alongside the original.

Responsibilities
  • Review AI outputs against current legal review statutes, case law, or policy for Legal Expert (Antitrust & Competition Law) assignments.
  • Verify citations, jurisdictions, and dates against authoritative sources.
  • Flag risky reasoning, missed exceptions, and policy-adherence gaps with severity tags.
  • Capture the corrected analysis or memo paragraph so the modeling team can train on it.
  • Adjudicate disputed treatments against published authority or firm policy.
  • Maintain reviewer-quality scores in inter-rater calibration cycles.
Qualifications
  • Active or recent qualification in legal review or an adjacent practice for Legal Expert (Antitrust & Competition Law) work.
  • Hands-on experience drafting, reviewing, or advising on real matters.
  • Comfort applying multi-page rubrics consistently across long batches.
  • Clear written reasoning that cites authority and names the rule being applied.
  • Reliable async availability for at least 10 hours per week.
Example tasks
  • Verify the citations in a model's legal review memo and flag any miscites with severity.
  • Grade a model's statutory reasoning on a complex fact pattern and rate the analysis.
  • Adjudicate a disputed treatment between two reviewers using current authority.
  • Audit a 25-row batch for rubric consistency and report drift to the program lead.
Nice to have
  • Bar admission or legal-equivalent credential in a relevant jurisdiction.
  • Prior experience reviewing AI-assisted legal-research or compliance tooling.
  • Bilingual experience for cross-jurisdiction matters.
Skills
  • Legal research
  • Citation review
  • Statutory analysis
  • Policy reasoning
  • Legal review
  • Legal
Work model

Remote — US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

Hourly rate confirmed after the interview process.

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