Principal AI Security Analyst

Waters
Milford, MA, United States
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$120,500.0 - $200,500.0
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cyber Security Python (Programming Language) Machine Learning AI Infrastructure Large Language Models Rate Limiting Containerization Palo Alto Networks
+2 more
Data Management Machine Learning Operations

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. 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

Requirements

  • 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

Benefits & conditions

$120,500.00 - $200,500.00

About the company

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.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:20 min

Utilizing industry threat models for AI security

Balázs Kiss · World Congress 2023

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Defining goals for multi-tenant rate limiting

Jan Mensch Jan Mensch · World Congress 2026 Europe

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Introduction to cloud-native application developer security

Micah Silverman · World Congress 2022

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Outline of free tools for Microsoft Azure

Radu Vunvulea Radu Vunvulea · World Congress 2022

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Addressing active AI incident remediation and broad ecosystem support

Matthew Brady Matthew Brady · World Congress 2026 Europe

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Transitioning to Layer 7 rate limiting safeguards

Jan Mensch Jan Mensch · World Congress 2026 Europe

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