Job description

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. • 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 REQUIRED • 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) PREFERRED • 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 Waters Corporation (NYSE:WAT) is a global leader in life sciences and diagnostics, dedicated to accelerating the benefits of pioneering science through analytical technologies, informatics, and service. With a focus on regulated, high-volume testing environments, our innovative portfolio harnesses deep scientific expertise across chemistry, physics, and biology. We collaborate with customers around the world to advance the release of effective, high-quality medicines, ensure the safety of food and water, and drive better patient outcomes by detecting diseases earlier, managing routine infections, and combating antibiotic resistance. Through a shared culture of relentless innovation, our passionate team of ~16,000 colleagues turn scientific challenges into breakthroughs that improve lives worldwide. Diversity and inclusion are fundamental to our core values at Waters Corporation. It benefits our employees, our products, our customers and our community. Waters complies with all applicable federal, state, and local laws. Qualified applicants are considered without regard to sex, race, color, ancestry, national origin, citizenship status, religion, age, marital status (including civil unions), military service, veteran status, pregnancy (including childbirth and related medical conditions), genetic information, sexual orientation, gender identity, legally recognized disability, domestic violence victim status, or any other characteristic protected by law. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. All hiring decisions are based solely on qualifications, merit, and business needs at the time. ai ai_security cybersecurity infosec information_security

Requirements

Must-haves

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)

Nice-to-haves

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
ai ai_security cybersecurity infosec information_security

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