AI Jailbreak & Prompt-Injection Security Expert

Remotebridge; United States; Remote; USD 110,000 - 165,000; Full time

Job summary

Remotebridge is seeking an AI Jailbreak & Prompt-Injection Security Expert for a remote contracting engagement. You will design evaluation methodologies focusing on ethical jailbreaks, LLM red teaming, prompt-injection and tool-use abuse scenarios.

You will develop cross-domain elicitation strategies, build regression test suites, and create robust evaluation frameworks to stress-test AI models against real-world adversarial threats, translating findings into actionable safety improvements.

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 within the AI security community through published research or open-source tools.
• Exceptional written and verbal communication skills with a focus on documentation and collaboration.
• Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools.

Responsibilities

• 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 cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
• Develop, maintain, and update regression test suites that test jailbreak susceptibility and prompt-injection vulnerabilities.
• Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats and enhance 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 technical and non-technical audiences.

Skills

Adversarial ML

LLM red teaming

AI safety evaluation

Technical reporting

Cross-functional collaboration

Education

MS/PhD in CS or cybersecurity

Tools

Threat modeling tools

Adversarial testing tools

Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert

Role Type: Contractor

Location: Remote

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.