AI Security Red Team Engineer

Check Point Software; Washington (District of Columbia); On-site; USD 140,000 - 220,000; Full time

Job summary

Check Point Software is seeking an AI Security Engineer to join our Red Team and help push the boundaries of AI security for enterprise clients. You’ll run cutting-edge assessments, develop testing methodologies, and build automation to scale testing, working across research and product teams to translate findings into practical improvements.

The role requires deep knowledge of AI/ML security, threat modeling, and hands-on debugging across web, API, and network layers.

Qualifications

• Experience in red teaming, penetration testing, security assessments, or bug bounty programs.
• Ability to find vulnerabilities by hand, not only with tools.
• Strong knowledge of web, API, and network security fundamentals.
• Deep understanding of LLM vulnerabilities and prompt injection risks.
• Experience with threat modeling complex systems and architectures.
• Experience developing automated tooling to improve testing workflows.

Responsibilities

• Deliver AI red team security assessments for enterprise clients.
• Define project scope, testing requirements, and success criteria with clients.
• Assess AI systems including text-based LLMs and multimodal agents.
• Develop automation to scale testing efforts.
• Write detailed security reports with actionable findings and remediation recommendations.
• Present findings to technical and executive stakeholders.

Skills

Red teaming

Penetration testing

Web/API security

LLM vulnerabilities

Threat modeling

Automated tooling

Job description

Check Point Software is seeking an AI Security Engineer to join our Red Team and help push the boundaries of AI security for enterprise clients. You’ll run cutting-edge assessments, develop testing methodologies, and build automation to scale testing, working across research and product teams to translate findings into practical improvements.

The role requires deep knowledge of AI/ML security, threat modeling, and hands-on debugging across web, API, and network layers.