Principal Cyber AI Engineer

Key Responsibilities

• Design, develop, and optimize AI-security-specific threat models, tools, and solutions for threat identification, prediction, and prevention.
• Implement and secure machine learning models, GenAI models, and AI techniques to enhance threat detection, monitoring, and risk scoring.
• Integrate AI security tools and technologies across cybersecurity architectures, collaborating with data scientists, security engineers, and other stakeholders.
• Analyze AI security incident data to refine and improve AI models and methodologies.
• Provide technical leadership and mentorship to junior engineers in AI and machine learning.
• Ensure alignment and compliance with industry standards (NIST AI-RMF, ISO 42001, OWASP Top 10 for LLMs) and advanced security architectures (Agentic, MCP).
• Stay abreast of emerging trends and advancements in AI and cybersecurity.

Required Qualifications

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related discipline is required.
• 5+ years of experience in AI-focused cybersecurity in an enterprise environment.
• Expertise in Python, R, Java, or similar programming languages.
• Deep understanding of machine learning, neural networks, and application to security systems.
• Hands-on experience with AI security technologies (intrusion detection, anomaly detection, threat intelligence).
• 3+ years’ experience in Azure or AWS cloud-native services, architectures, and tools.
• Expertise in enterprise architectures (including cloud-native and AI architecture patterns).
• Advanced knowledge of security and governance frameworks (NIST AI-RMF, ISO 42001, OWASP Top 10 for LLM).
• Strong communication and collaboration skills.

Preferred Qualifications

• Experience with implementing OWASP Top 10 LLM Threats in practice with any industry or open-source product.
• Working experience in Threat Modeling
• Experience with agentic and Model Context Protocol (MCP) architectures.
• Demonstrated ability to lead cross-functional technical teams.
• Track record of published research or thought leadership in AI security.