Remote AI Workflow Reviewer — Public Sector Policy & Risk

AuraOne, Inc.; United States; Remote; USD 34,000 - 55,000; Full time

Job summary

AuraOne, Inc. is seeking a remote Enterprise Client Partner for Public Sector — AI Workflow Review to evaluate AI outputs within U.S. government specialist operations.

You will review workflows, playbooks, and firm policy to ensure alignment with business needs. Responsibilities include grading tone, escalation logic, and stakeholder fit; flagging operational risks and policy-adherence gaps; capturing the right next steps so the modeling team can train on it; and maintaining inter-rater

Qualifications

• Direct experience in enterprise client partner U.S. government specialist operations on real teams for Enterprise Client Partner, Public Sector — AI Workflow Review (Remote).
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning that names the policy or workflow being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against enterprise client partner U.S. government workflows, playbooks, and firm policy for Enterprise Client Partner, Public Sector — AI Workflow Review (Remote) 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

Job description

AuraOne, Inc. is seeking a remote Enterprise Client Partner for Public Sector — AI Workflow Review to evaluate AI outputs within U.S. government specialist operations.

You will review workflows, playbooks, and firm policy to ensure alignment with business needs. Responsibilities include grading tone, escalation logic, and stakeholder fit; flagging operational risks and policy-adherence gaps; capturing the right next steps so the modeling team can train on it; and maintaining inter-rater