Principal Cyber AI Engineer

Job Description

The Cyber AI Engineer will drive the development and optimization of advanced tools, processes, and workflows to predict, detect, and prevent AI-specific threats. This hands-on technical leadership role combines deep research in AI security with close collaboration across teams to integrate AI security capabilities into robust cybersecurity architectures.

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

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