Content Editor

AI Trainer Jobs; United States; Remote; USD 97,000 - 138,000; Part time

Job summary

AuraOne seeks a Content Editor for a remote review track evaluating AI outputs across content editor operations. Reviewers rate workflow correctness, policy adherence, and stakeholder fit, flag risks, and document the next steps for model training.

The role emphasizes judging tool usage, enterprise agent behavior, and applying consistent rubrics to long batches, with at least 10 hours per week available asynchronously. Contractors are US-eligible.

Qualifications

• Direct working experience in content editor specialist operations on real teams.
• Ability to apply 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 content editor specialist operations workflows, playbooks, and firm policy for Content Editor 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.

Skills

Content Editor operations

Policy adherence

Attention to detail

Prompt analysis

Async availability

Tools

AI-assisted workflow tooling

Job description

Content Editor is a remote review track for evaluating AI outputs across content editor specialist operations 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

Content Editor is a remote review track for evaluating AI outputs across content editor specialist operations workflows.

About the role

Content Editor is a remote review track for evaluating AI outputs across content editor specialist operations 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.
Content Editor specialist operations 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 content editor specialist operations workflows, playbooks, and firm policy for Content Editor 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 content editor specialist operations on real teams for Content Editor 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 content editor specialist operations 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
• Content Editor specialist operations

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.

Placement timing depends on program demand and reviewer confirmation.