Principal AI Security Analyst

As a Principal AI Security Analyst, you will be the organization's deepest subject-matter expert at the intersection of artificial intelligence and cybersecurity. You will lead the security review of AI/ML systems, manage our AI security toolchain, identify emerging threats unique to large-scale models, and build the frameworks that keep our AI infrastructure resilient against adversarial attacks. This is a high-visibility, high-autonomy role that shapes how the company thinks about AI risk.

Responsibilities

• Own end-to-end threat modeling for AI and ML systems, including LLMs, training pipelines, and inference infrastructure
• Administer and tune Palo Alto Networks AI Runtime Security (AIRS) to detect and block adversarial inputs, prompt injection, and model abuse in real time
• Manage AI Access Security policies to govern employee use of third-party AI applications - enforcing DLP, acceptable-use rules, and shadow-AI visibility
• Integrate an AI gateway layer to apply rate limiting, access controls, and observability across LLM API traffic
• Research and operationalize defenses against adversarial attacks - model extraction, data poisoning, jailbreaking, and membership inference
• Lead red-team exercises targeting AI systems and synthesize findings into actionable security roadmaps
• Define and maintain security standards, policies, and controls specific to AI model development and deployment
• Partner with ML engineering, platform, and product teams to embed security requirements from design through production
• Evaluate third-party AI tools, APIs, and vendors for supply-chain and data-handling risk
• Work with other security team members in AI governance discussions, including compliance with EU AI Act and NIST AI RMF
• Mentor other team members; set technical direction for the AI security practice

• 8+ years in cybersecurity with 3+ years focused on AI/ML security
• Hands-on experience with Palo Alto Networks AIRS or AI Access Security
• Deep understanding of LLM architectures and common vulnerability classes
• Proficiency in Python; ability to review model code and ML pipelines
• Experience with threat modeling frameworks (STRIDE, PASTA, or similar)
• Track record driving cross-functional security programs at scale
• Cloud-native environment experience (AWS, GCP, or Azure)

• Palo Alto Networks certifications (PCNSE, PCCSE, or equivalent)
• Experience deploying AI gateways (Portkey, Kong AI, or similar)
• Published research or CVEs related to AI/ML security
• Familiarity with differential privacy or model watermarking
• CISSP, OSCP, or equivalent certifications