Product Manager/Product Owner at AuraOne

AI Trainer Jobs; Northern (KY); Hybrid; USD 96,000 - 138,000; Full time

Job summary

AI Trainer Jobs seeks a Product Manager/Product Owner to oversee a remote review track evaluating AI outputs across product management workflows. You will grade workflow correctness, policy adherence, and stakeholder fit, and document next steps for model training.

Ideal candidates have hands-on product management experience, the ability to apply multi-page rubrics consistently, and clear written reasoning naming the policy or workflow used. Remote, contractor role with flexible weekly hours.

Qualifications

• Direct working experience in product management on real teams.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning that names the policy or workflow applied.
• Strong attention to detail and the ability to flag when a prompt is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current product management workflows and firm policy.
• 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.

Skills

Product management

Policy adherence

Rubrics judgment

Written reasoning

Async availability

Job description

Role details

Product Manager/Product Owner is a remote review track for evaluating AI outputs across product management workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.

Category: Enterprise Workflow & Tool Use · Pay: $85 / hr · Location: Remote — US-eligible · Contractor

Product Manager/Product Owner is a remote review track for evaluating AI outputs across product management workflows.

About the role

Product Manager/Product Owner is a remote review track for evaluating AI outputs across product management workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.
Product management AI has to fit into an actual day at work. AuraOne uses experienced operators to grade outputs the way a senior peer would — checking workflow, policy, and the unwritten rules that decide whether a task actually gets done.
Judge tool-use tasks and enterprise agent behavior. Operational judgment is the skill.

Responsibilities

• Review AI outputs against current product management workflows, playbooks, and firm policy for Product Manager/Product Owner 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.

What you should bring

• Direct working experience in product management on real teams for Product Manager/Product Owner 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.

Example tasks

• Grade a model's response to a real product management ticket and rate workflow, tone, and escalation.
• Flag a missed escalation with the right severity tag and corrected next step.
• Adjudicate a disputed playbook call between two reviewers using firm guidance.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• Prior experience training, calibrating, or QA-ing operations teams.
• Familiarity with AI-assisted workflow tooling and its failure modes.
• Bilingual experience for cross-region operations.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Operational review
• Policy adherence
• Workflow judgment
• Stakeholder communication
• Product management