Expert in Red Teaming and AI Safety
We are seeking analytical professionals to test and evaluate AI-generated content, identify vulnerabilities, and ensure compliance with safety and quality standards.
Key Responsibilities:
* Conduct Red Teaming exercises to identify adversarial outputs from large language models (LLMs).
* Evaluate AI prompts across multiple domains to uncover potential failure modes.
* Develop and apply test cases to assess accuracy, bias, toxicity, hallucinations, and misuse potential in AI-generated responses.
* Collaborate with data scientists to report risks and suggest mitigations.
* Perform manual QA and content validation across model versions, ensuring factual consistency and guideline adherence.
* Create evaluation frameworks and scoring rubrics for prompt performance and safety compliance.
Requirements:
* Proven experience in AI red teaming, LLM safety testing, 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 behavior's, failure modes, and model evaluation metrics.
* Excellent critical thinking, pattern recognition, and analytical writing skills.
Preferred Qualifications:
* Prior work with teams like Open AI or other LLM safety initiatives.
* Experience in risk assessment, red team security testing, or AI policy & governance.