AVP - AI Security

VP, Cybersecurity

classic infrastructure/mobile security

Key Responsibilities

Lead rigorous pre- and post-deployment testing of Company's AI Security products to ensure they effectively prevent, detect and respond to AI-specific attacks (e.g., adversarial inputs, model extraction, prompt injection)

Design and execute evaluations of our AI protection tools, simulating real-world threat scenarios targeting LLMs, ML pipelines, and AI agentic systems

Collaborate with product and engineering to continuously improve defenses based on security test results, threat modeling, and vulnerability discovery

Oversee security validation pipelines across all product lines, with a special focus on security assurance for AI-focused solutions

Build and scale a security assurance function that includes penetration testing, red teaming, and continuous vulnerability scanning across mobile, cloud, and AI assets

Ensure the integration of SSDLC practices, including threat modeling and static/dynamic analysis, into the engineering workflow

Present the security findings to executive leadership, clients, and auditors, with clear risk analysis and actionable recommendations

Guide a growing team of security analysts and researchers focused on protecting both internal infrastructure and client-facing security capabilities

Align testing frameworks and documentation with industry standards (e.g., NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10)

Continuously monitor emerging trends in cybersecurity, AI/ML threats, adversarial techniques, and defense frameworks, proactively incorporating mitigations into product design ensuring Company's products stay ahead of evolving attack vectors

Required Qualifications, Experience & Skills

Bachelor's or Master's degree in Computer Science, Cybersecurity, Information Security, or a related field; certifications such as CISSP, OSCP, or GIAC are a strong plus

8+ years of experience in cybersecurity, including 3+ years in leadership roles involving product or platform security

Proven expertise in vulnerability assessment, penetration testing, and security assurance across cloud-native and mobile platforms

Experience conducting or overseeing adversarial evaluations of AI/ML systems, including model-level attacks, prompt injection, and data poisoning

Familiarity with modern AI architectures (e.g., LLMs, agentic AI frameworks) and their unique security challenges

Practical knowledge of security testing tools such as Burp Suite, Nessus, Metasploit, OWASP ZAP, and optionally AI-focused tools like IBM ART, CleverHans, or PrivacyRaven

Deep understanding of SSDLC, secure architecture, and post-deployment hardening practices

Track record of successfully working with engineering, product, and compliance teams to integrate security into the software lifecycle

Strong leadership, communication, and stakeholder management skills; experience representing cybersecurity in front of customers, regulators, or exec teams.

Preferred Skills (Nice to have)

Familiarity with AI-specific security frameworks like NIST AI RMF, ISO/IEC 42001, and OWASP Top 10 for LLMs

Exposure to security testing of agent-based AI systems and tool-use frameworks (e.g., LangChain, AutoGen, ReAct)

Understanding of threat intelligence, anomaly detection, and red teaming techniques in AI contexts