Full Description

• Execute AI-focused penetration testing engagements that include manual penetration testing of systems incorporating AI/ML, objective-based testing of AI-driven features, and coverage of both traditional and AI-centric attack surfaces.

• Perform threat modeling for AI-powered software systems, evaluate AI-related business logic, and conduct architecture reviews. Focus on adversarial ML vectors, prompt-based vulnerabilities, and other AI-specific security risks.

• Develop and improve AI-driven tools and methodologies for offensive security tasks such as discovery, exploitation, fuzzing, and adversarial ML testing, emphasizing web apps, APIs, and mobile clients.

• Demonstrate AI penetration testing findings to technical and non-technical audiences, including live demos.

• Collaborate with engineering, development, and security teams to communicate findings, lead remediation discussions, and advise on secure AI model development and deployment best practices.

• Research emerging AI attack techniques and evaluate their potential impact, identify vulnerabilities, and provide actionable recommendations to strengthen AI defenses.

• Collaborate with internal Red Teams, SOC analysts, and AI security researchers, sharing insights and data to enhance AI-driven offensive security methodologies. Refine existing AI red teaming approaches by integrating new adversarial ML techniques and proven exploitation tactics.

• Act independently on AI penetration testing with minimal oversight, guiding engagements from planning through execution and reporting.

Qualifications: The skills, abilities, specific knowledge, education, and minimum experience necessary to perform this job.

• Minimum three (3) years of recent penetration testing experience focused on APIs, web applications, and mobile applications. Experience with AI model testing or AI security is highly desirable.

• Proven background in AI red teaming and adversarial attack development, including prompt engineering attacks, LLM-based vulnerability analysis, and model evasion techniques.

• Proficiency with penetration testing tools (e.g., Burp Suite Pro, Netsparker, Checkmarx) and AI security frameworks (e.g., TensorFlow, PyTorch, LLM APIs, LangChain).

• Strong communication and presentation skills to explain AI-related vulnerabilities to technical and non-technical stakeholders and drive remediation.

• One or more major ethical hacking certifications (e.g., GWAPT, CREST, OSWE, OSWA) and certifications or training in AI security techniques.