AI Red Teamer Job Description
We are seeking highly analytical and detail-oriented professionals with hands-on experience in AI model evaluation, prompt assessment, and quality assurance. The ideal candidate will help us rigorously test and evaluate AI-generated content to identify vulnerabilities, assess risks, and ensure compliance with safety, ethical, and quality standards.
* Conduct thorough testing of large language models (LLMs) to identify adversarial outputs and potential failure modes.
* Evaluate AI prompts across multiple domains (e.g., finance, healthcare, security) to uncover biases, inaccuracies, and misuse potential.
* Develop and apply test cases to assess accuracy, bias, toxicity, hallucinations, and misalignment in AI-generated responses.
* Collaborate with data scientists, safety researchers, and prompt engineers to report risks and suggest mitigations.
* Perform manual QA and content validation across model versions, ensuring factual consistency, coherence, and guideline adherence.
* Create evaluation frameworks and scoring rubrics for prompt performance and safety compliance.
* Document findings, edge cases, and vulnerability reports with high clarity and structure.
Requirements:
* Proven experience in AI model testing, LLM safety evaluation, or adversarial prompt design.
* Familiarity with prompt engineering, NLP tasks, and ethical considerations in generative AI.
* Strong background in Quality Assurance, content review, or test case development for AI/ML systems.
* Understanding of LLM behaviors, failure modes, and model evaluation metrics.
* Excellent critical thinking, pattern recognition, and analytical writing skills.
* Ability to work independently, follow detailed evaluation protocols, and meet tight deadlines.
Preferred Qualifications:
* Prior work with teams focused on AI safety and responsible AI development.
* Experience in risk assessment, red team security testing, or AI policy & governance.
* Background in linguistics, psychology, or computational ethics is a plus.