Job Description
We are seeking analytical professionals to conduct rigorous testing and evaluation of AI-generated content. This includes identifying vulnerabilities, assessing risks, and ensuring compliance with safety, ethical, and quality standards.
Key Responsibilities:
* Red Teaming: Conduct exercises to identify adversarial, harmful, or unsafe outputs from large language models (LLMs).
* Prompt Evaluation: Stress-test AI prompts across multiple domains (e.g., finance, healthcare, security) to uncover potential failure modes.
* Test Case Development: Develop and apply test cases to assess accuracy, bias, toxicity, hallucinations, and misuse potential in AI-generated responses.
* Collaboration: Work with data scientists, safety researchers, and prompt engineers to report risks and suggest mitigations.
* Manual QA: Perform manual Quality Assurance and content validation across model versions, ensuring factual consistency, coherence, and guideline adherence.
Requirements:
* Experience: Proven experience in AI red teaming, LLM safety testing, or adversarial prompt design.
* Familiarity: Familiarity with prompt engineering, NLP tasks, and ethical considerations in generative AI.
* Background: Strong background in Quality Assurance, content review, or test case development for AI/ML systems.
* Knowledge: Understanding of LLM behavior's, failure modes, and model evaluation metrics.
* Skills: Excellent critical thinking, pattern recognition, and analytical writing skills.
Preferred Qualifications:
* Industry Experience: Prior work with teams like Open AI, Anthropic, Google DeepMind, or other LLM safety initiatives.
* Risk Assessment: Experience in risk assessment, red team security testing, or AI policy & governance.
A background in linguistics, psychology, or computational ethics is a plus.