Red-Teaming Quality Assurance Lead (QAL)

About this role

In this hourly, remote contractor role, you will work as a Red-Teaming Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across AI red-teaming and safety-evaluation projects. You will review AI-generated safety evaluations, adversarial prompts, risk analyses, and trainer/QA work; evaluate output quality against project guidelines; provide precise written feedback; and ensure that all contributors follow the expected quality standards. You will assess work for risk identification, adversarial reasoning, policy awareness, safety taxonomy alignment, prompt quality, scenario realism, vulnerability coverage, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong AI safety/red-teaming judgment, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your red-teaming quality leadership will directly help improve the world’s premier AI models by ensuring that safety training data is realistic, nuanced, policy-aligned, well-documented, and useful for identifying model vulnerabilities. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.