Prompt Robustness Failure Analysis Reviewer

AuraOne Human Data; Deutschland; Remote; EUR 49,000 - 98,000; Full time

Job summary

AuraOne Human Data is seeking a Prompt Robustness Failure Analysis Reviewer to remotely assess prompts and responses against our quality rubric. You will compare paired outputs, label edge cases, and provide structured feedback to retrain models.

As a contractor, you will work asynchronously for at least 10 hours per week, evaluating model outputs, tagging issues, and documenting recurring failure modes to inform future training and rubric updates.

Qualifications

• Prior evaluation, annotation, or human-rater experience on prompt robustness failure analysis evaluation or adjacent content for Prompt Robustness Failure Analysis Reviewer 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.

Responsibilities

• Evaluate prompt robustness failure analysis evaluation model outputs against a versioned rubric and assign severity tags for Prompt Robustness Failure Analysis Reviewer 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.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Prompt evaluation

Rubric-based annotation

Inter-rater calibration

Attention to detail

Async availability

Job description

Prompt Robustness Failure Analysis Reviewer is a remote evaluation track for reviewing prompt robustness failure analysis 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.

Why this role matters

AI data reviewers help turn prompt robustness failure analysis evaluation outputs into auditable labels, rationales, and regression cases for AuraOne Human Data.

Responsibilities

• Evaluate prompt robustness failure analysis evaluation model outputs against a versioned rubric and assign severity tags for Prompt Robustness Failure Analysis Reviewer 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.
• Document recurring failure modes so the modeling team can target them in the next training run.

Qualifications

• Prior evaluation, annotation, or human-rater experience on prompt robustness failure analysis evaluation or adjacent content for Prompt Robustness Failure Analysis Reviewer 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.

Example tasks

• Compare two prompt robustness failure analysis 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.

Nice to have

• 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.

Skills

• Model output evaluation
• Rubric-based annotation
• Severity tagging
• Inter-rater calibration
• Prompt Robustness Failure Analysis evaluation
• Frontier evaluation
• Rubric calibration
• Failure analysis
• Prompt
• Robustness

Work model

Remote --- US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

Hourly rate confirmed after the interview process.

Application process

Apply through AuraOne's specialist intake for role-specific routing and review. Final project scope, schedule, and contractor terms are confirmed before placement.