Agent Workflow Evaluator

AI Trainer Jobs; United States; Remote; USD 28,000 - 55,000; Full time

Job summary

AI Trainer Jobs is seeking an Agent Workflow Evaluator for a remote evaluation track. You will review agent workflow evaluation prompts and responses against a quality rubric, compare paired outputs, and provide structured feedback to help retrain models.

Responsibilities include labeling edge cases, flagging hallucinations, and documenting rationales and regression cases. This is a contractor role with flexible hours and compensation arranged after interview.

Qualifications

• Prior evaluation, annotation, or human-rater experience on agent workflow evaluation or adjacent content.
• 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.

Responsibilities

• Evaluate agent workflow evaluation model outputs against a versioned rubric and assign severity tags.
• Compare paired responses and pick the stronger answer with 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.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.

Skills

Evaluation experience

Annotation experience

Written reasoning

Attention to detail

Async availability

Remote work

Job description

About the role

Agent Workflow Evaluator is a remote evaluation track for reviewing agent workflow 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 agent workflow 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 agent workflow evaluation model outputs against a versioned rubric and assign severity tags for Agent Workflow 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.
• Maintain reviewer-quality scores by calibrating against gold-standard examples each week.

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 agent workflow evaluation or adjacent content for Agent Workflow 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 agent workflow 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
• Agent Workflow evaluation
• Cross-cutting evaluation roles
• AI evaluation
• Rubric writing
• Expert review