Role Title: AI Jailbreak & Prompt-Injection Security Expert
Role Type: Contract
Location: Remote
Required Skills:
Ethical Jailbreaks
LLM Red Teaming
Prompt Injection
Tool-Use Abuse
In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters.
Scope of Work:
Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.
Preferred Qualifications:
2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.
Summary
Design and run adversarial tests for AI systems, including ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse. Build regression suites and evaluation frameworks, then document findings for technical and non-technical stakeholders. Preferred: 2+ years in adversarial ML/security, advanced degree or equivalent, and strong communication.
Responsibilities
Design methodologies for AI safety evaluation; create cross-domain elicitation strategies; develop regression test suites; construct evaluation frameworks; collaborate with stakeholders; document findings.
Qualifications
Preferred: 2+ years in adversarial ML/LLM red teaming/AI safety; proven vulnerability research; advanced degree or equivalent; recognition in AI security community; strong communication; cross-functional experience a plus; familiarity with LLM architectures/tools desirable.
Education requirements
Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or relevant discipline, or equivalent operational/professional background.
Experience requirements
Preferred: 2+ years in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain; proven vulnerability research.