Remote Corporate Attorney — AI Review & Citations

AuraOne; United States; Remote; USD 55,000 - 83,000; Full time

Job summary

AuraOne is seeking a Corporate Attorney reviewer to evaluate AI-generated legal outputs for BigLaw-style assignments. This remote contractor role focuses on citation accuracy, jurisdiction checks, and policy adherence, with emphasis on precise reasoning and sourced authorities.

You will work asynchronously for at least 10 hours per week, reviewing model outputs, flagging issues, and documenting corrected analyses so the modeling team can train on high-quality data.

Qualifications

• Active or recent qualification in legal review or an adjacent practice for Corporate Attorney (BigLaw Firms) 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.

Responsibilities

• Review AI outputs against current legal review statutes, case law, or policy for Corporate Attorney (BigLaw Firms) 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

Education

Bar admission

J.D. or equivalent

Job description

AuraOne is seeking a Corporate Attorney reviewer to evaluate AI-generated legal outputs for BigLaw-style assignments. This remote contractor role focuses on citation accuracy, jurisdiction checks, and policy adherence, with emphasis on precise reasoning and sourced authorities.

You will work asynchronously for at least 10 hours per week, reviewing model outputs, flagging issues, and documenting corrected analyses so the modeling team can train on high-quality data.