We are seeking analytical professionals with hands-on experience in Red Teaming, Prompt Evaluation, and AI/LLM Quality Assurance.
Key Responsibilities:
* Conduct Red Teaming exercises to identify adversarial outputs from large language models.
* Evaluate and stress-test AI prompts across multiple domains to uncover potential failure modes.
* Develop test cases to assess accuracy, bias, toxicity, hallucinations, and misuse potential 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 to ensure factual consistency, coherence, and guideline adherence.
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, failure modes, and model evaluation metrics.
* Critical thinking, pattern recognition, and analytical writing skills.
Preferred Qualifications:
* Prior work with teams like Open AI, Anthropic, Google DeepMind, or other LLM safety initiatives.
* Experience in risk assessment, red team security testing, or AI policy & governance.
A background in linguistics, psychology, or computational ethics is a plus.