Job Title

Job Description:We are seeking highly analytical and detail-oriented professionals with hands-on experience in Red Teaming, Prompt Evaluation, and AI/LLM 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. Key Responsibilities:Conduct Red Teaming exercises to identify adversarial, harmful, or unsafe outputs from large language models (LLMs).Evaluate and stress-test AI prompts across multiple domains (e.g., finance, healthcare, security) 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, 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 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 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 like OpenAI, Anthropic, Google DeepMind, or other LLM safety initiatives.Experience in risk assessment, red team security testing, or AI policy & governance. Background in linguistics, psychology, or computational ethics is a plus.