
AI Red Teamer – LLM Generalist
Posted Sep 15

Posted Sep 15
This is a fully remote position, open to applicants in United States.
• Conduct stress tests on large language models by deliberately attempting to break them.
• Create innovative, adversarial prompts that reveal unsafe content, biases, ineffective guardrails, hallucinations, vulnerabilities to prompt injection, and unanticipated behaviors.
• Assess models in various areas including content safety, CBRN, cybersecurity, persuasion and influence operations, child safety, self-harm, over-dependence, and regulatory compliance.
• Evaluate text, image, voice, and agentic model capabilities as project requirements dictate.
• Develop multi-turn scenarios to rigorously test AI safety measures.
• Identify ways to bypass safety filters, restrictions, and defenses using techniques such as jailbreak, evasion, and prompt injection.
• Investigate edge cases to elicit disallowed, harmful, or inaccurate outputs.
• Assess and score model responses using structured harm taxonomies and severity scales.
• Document experiments meticulously, detailing methods, reasoning, and results.
• Review and enhance adversarial prompts created by team members.
• Contribute to the advancement of harm taxonomy, calibration exercises, and inter-rater reliability initiatives.
• Collaborate with engineers, data scientists, and researchers to disseminate findings and bolster defenses.
• Regularly handle potentially distressing content.
• Keep abreast of the latest jailbreaks, attack strategies, and evolving model behaviors.
• Support Handshake AI's collaboration with premier AI research laboratories to enhance model safety and resilience.
• Extensive hands-on experience with various LLMs, including ChatGPT, Claude, Gemini, and open-source models.
• An innate ability to craft adversarial prompts; knowledge of jailbreak or evasion techniques is a significant advantage.
• Creative and adversarial problem-solving abilities.
• Clear and thoughtful written communication skills.
• Strong ethical judgment and the capacity to distinguish adversarial thinking from personal morals.
• Self-motivated, collaborative, and at ease in feedback-rich environments.
• A sense of curiosity, persistence, and comfort with frequent setbacks in experimentation.
• Candidates must be capable of professionally and sustainably engaging with harmful material.
• Familiarity with Python or other scripting languages.
• Experience with LLM APIs or evaluation tools.
• Competence in structured data annotation and rubric-based scoring.
• Previous work in trust and safety, content moderation, QA, or security research.
• Expertise in a high-risk field such as cybersecurity, chemistry, biology, medicine, law, or finance.
• Ability to work remotely from the United States, Monday through Friday, for 40 hours per week.
• Must be authorized to work lawfully in the United States for Handshake.
• Must not require employment visa sponsorship, as specified in the application guidelines.
• Support resources are available for managing exposure to disturbing content.
• Cash compensation ranges from $32 to $95 per hour.
• Opportunity for remote work from the United States.
• Full-time commitment of 40 hours per week.
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