Customer Support Escalation AI Evaluator

AuraOne; United States; On-site; USD 34,000 - 55,000; Full time

Job summary

AuraOne seeks a remote Customer Support Escalation AI Evaluator contractor to review prompts and model outputs. You will compare paired responses, assign severity, and write rationales to guide retraining efforts.

The role focuses on labeling edge cases, detecting hallucinations, and feeding structured feedback to the modeling team. Candidates should demonstrate prior evaluation experience, ability to apply long-form rubrics consistently, and clear written reasoning.

Qualifications

• Prior evaluation, annotation, or human-rater experience on customer support escalation AI evaluation.
• Ability to apply rubrics consistently across long batches.
• Clear written reasoning citing rubric clauses.
• Strong attention to detail with ability to flag prompt issues.
• Reliable asynchronous availability for at least 10 hours per week.

Responsibilities

• Evaluate customer support escalation AI evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and select the stronger answer with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them back to the program team for rubric updates.

Skills

Evaluation experience

Rubric application

Written reasoning

Attention to detail

Async availability

Job description

About the role

Customer Support Escalation AI Evaluator is a remote evaluation track for reviewing customer support escalation ai evaluation prompts and responses against AuraOne's quality rubric. Reviewers compare paired outputs, label edge cases, and write the kind of structured feedback the modeling team can use to retrain.
AI data reviewers help turn customer support escalation ai evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.
Review frontier model outputs. Judge benchmark failures and calibrate other evaluators.

Responsibilities

• Evaluate customer support escalation ai evaluation model outputs against a versioned rubric and assign severity tags for Customer Support Escalation AI Evaluator assignments.
• Compare paired responses and pick the stronger answer with a written rationale.
• Label hallucinations, instruction-following failures, and unsafe content with structured tags.
• Capture ambiguous prompts and route them back to the program team for rubric updates.

Role details

Track Evaluation & annotation Work model Remote Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Prior evaluation, annotation, or human-rater experience on customer support escalation ai evaluation or adjacent content for Customer Support Escalation AI Evaluator work.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the issue and the rubric clause 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.

Role signals

Example tasks

• Compare two customer support escalation ai evaluation model responses to the same prompt and pick the stronger one with rationale.
• Tag an unsafe response with the correct policy category and severity.
• Audit a 50-row batch for rubric consistency and report drift to the program lead.
• Propose a rubric clarification after spotting a recurring failure mode.

Useful experience

• Background in linguistics, content moderation, or trust & safety review.
• Experience with inter-rater agreement metrics and calibration cycles.
• Domain expertise that lets you spot subject-matter errors automated checks miss.

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

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Customer Support Escalation AI evaluation
• Enterprise operations
• AI evaluation
• Rubric writing
• Expert review