AI Red Teamer (Remote)

• Strong hands-on experience using multiple LLMs (ChatGPT, Claude, Gemini, open-source models, etc.)

• Intuition for crafting adversarial prompts; familiarity with jailbreak or evasion techniques is a strong plus

• Creative, adversarial problem-solving skills

• Clear and thoughtful written communication

• Strong ethical judgment and the ability to separate adversarial thinking from personal values

• Self-directed, collaborative, and comfortable in feedback-heavy environments

• Curiosity, persistence, and comfort with frequent failure in experimentation

• Familiarity with Python or other scripting languages

• Experience working with LLM APIs or evaluation tooling

• Comfort with structured data annotation and rubric-based scoring

• Prior work in trust and safety, content moderation, QA, or security research

• Subject matter expertise in any high-risk domain (cybersecurity, chemistry, biology, medicine, law, finance, etc.)

• You treat every model response as a hypothesis to challenge

• You can switch between creative free-association and rigorous documentation in the same session

• You go deep into unusual interests (fandoms, niche internet cultures, gaming exploits, Wikipedia rabbit holes, etc.)

• You come from a creative background: writing, visual art, improv, puzzle design, or similar

• You are energized by finding the thing nobody else thought to try

• You are genuinely passionate about AI and follow the space closely

This role involves regular and deliberate exposure to harmful content. You will encounter and intentionally generate content involving violence, self-harm, hate speech, sexually explicit material, child safety scenarios, and other categories of harmful output as part of structured adversarial testing. Candidates must be able to engage with this material professionally and sustainably. Support resources are available.

Handshake AI partners with leading AI research labs to make models safer and more robust. Our red teaming operations help identify vulnerabilities before they reach users, contributing directly to the responsible development of frontier AI systems.