Red-Teaming Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI hires and contracts contributors for specialized projects where human expertise helps improve how artificial intelligence works.

Creating an OpenTrain account is free, and contributors can build a profile that highlights their AI training experience, discover relevant opportunities, and apply in minutes.

About AI Safety Training

AI training is the human side of building modern artificial intelligence. Experts review model behavior, test edge cases, assess risks, and provide structured feedback that helps AI systems become safer, more reliable, and more useful.

Red-teaming is a specialized form of AI evaluation that probes models with adversarial prompts and misuse scenarios. Quality assurance leads help ensure this work is realistic, consistent, policy-aligned, and valuable for identifying vulnerabilities.

The Role

OpenTrain AI is hiring an expert Red-Teaming Quality Assurance Lead to oversee quality, consistency, and contributor performance across AI red-teaming and safety evaluation projects. You will review AI-generated safety evaluations, adversarial prompts, risk analyses, and trainer or QA submissions, then provide precise written feedback against project guidelines and rubrics.

Your assessments will cover adversarial reasoning, policy awareness, safety taxonomy alignment, scenario realism, vulnerability coverage, formatting, instruction-following, and rubric adherence. You will also identify recurring quality issues and help keep remote contributors aligned.

• Expert-level contract position
• Remote work setup
• United States hiring
• Part-time contractor engagement
• 20+ hours per week
• Up to $100 USD per hour

What You'll Do

You will combine detailed review, clear communication, and process support to maintain high standards across distributed red-teaming teams.

• Review adversarial prompts, model responses, risk classifications, safety analyses, policy explanations, and vulnerability reports for accuracy, realism, and usefulness.
• Spot-check trainer and QA submissions, escalate recurring issues, and reinforce quality standards across projects.
• Communicate updates, workflow changes, and review expectations to trainers and QAs through remote collaboration channels.
• Support onboarding, documentation, FAQs, trackers, calibration tasks, and process improvements.
• Help manage contributor activation and follow up when team members are inactive or not working consistently.

Required Qualifications

This role requires strong experience reviewing AI red-teaming, safety evaluations, or rubric-based quality work. You should be comfortable making consistent judgments against detailed standards and explaining those judgments in clear written English.

• Strong English communication skills and excellent attention to detail.
• Experience in AI safety, red-teaming, cybersecurity, trust and safety, content policy, risk analysis, model evaluation, content moderation, or related workflows.
• Familiarity with adversarial prompting, jailbreak patterns, harmful-content taxonomies, misuse scenarios, policy interpretation, and safety evaluation principles.
• Ability to assess adversarial prompts, risk analyses, and trainer or QA submissions for quality and policy alignment.
• Comfort evaluating work against detailed rubrics and leading or supporting remote teams.
• Experience with Discord, Google Sheets, Google Docs, trackers, dashboards, or project management systems.
• Availability for 20+ hours per week.

Helpful Background

The following experience or education can strengthen your fit for this specialized AI safety role, though the core requirement is relevant red-teaming, evaluation, or quality assurance expertise.

• Background in Computer Science, Cybersecurity, AI Safety, Trust & Safety, Public Policy, Psychology, Linguistics, Law, Security Studies, or Risk Analysis.
• Experience with AI training, LLM evaluation, safety evaluations, content moderation QA, policy QA, or rubric-based review.
• Familiarity with prompt injection, social engineering, cybersecurity abuse, fraud, self-harm safety, extremist content, misinformation, privacy risk, illicit behavior, bias, and model refusal behavior.

Why This Work Matters

This role supports the quality of safety training data used to improve leading AI models. Strong red-teaming QA helps ensure safety-focused datasets are realistic, nuanced, policy-aligned, well documented, and useful for identifying model vulnerabilities.

By reviewing difficult edge cases and strengthening contributor workflows, you will help shape how AI systems respond to harmful, risky, and adversarial situations.

How to Apply Through OpenTrain

Create a free OpenTrain account, build a profile that reflects your AI safety and quality assurance experience, and apply to this opportunity in minutes. OpenTrain helps contributors grow a durable portfolio in the fast-growing AI training and data-labeling industry.

• Confirm your United States eligibility and availability.
• Highlight relevant red-teaming, AI safety, cybersecurity, policy, evaluation, or QA experience.
• Showcase your ability to provide precise written feedback and work effectively with remote teams.