Remote Social Engineering Security Evaluator

AuraOne; United States; On-site; USD 55,104 - 82,656; Part time

Benefits offered by this job

Remote contractor

US-eligible

Contractor arrangement

Job summary

AuraOne is seeking a remote Social Engineering Security Evaluator contractor to review prompts and model outputs against a versioned rubric. You will compare paired responses, assign severity tags, and write rationales to support retraining.

The role emphasizes precise labeling of hallucinations, policy breaches, and unsafe content across long review batches. The ideal candidate has prior evaluation or annotation experience, strong attention to detail, clear written reasoning, and reliable async

Qualifications

• Prior evaluation, annotation, or human-rater experience in social engineering evaluation.
• Ability to apply multi-page rubrics consistently across long batches.
• Clear written reasoning naming the issue and rubric clause being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Evaluate social engineering security evaluation model outputs against a versioned rubric and assign severity tags for Social Engineering Security 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.
• Document recurring failure modes so the modeling team can target them in the next training run.

Skills

Evaluation experience

Attention to detail

Written rationale

Async availability

Job description

AuraOne is seeking a remote Social Engineering Security Evaluator contractor to review prompts and model outputs against a versioned rubric. You will compare paired responses, assign severity tags, and write rationales to support retraining.

The role emphasizes precise labeling of hallucinations, policy breaches, and unsafe content across long review batches. The ideal candidate has prior evaluation or annotation experience, strong attention to detail, clear written reasoning, and reliable async