Lead AI Security Architect

Rockwell Automation • Milwaukee, WI

5d • Hybrid

About The Position

Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better. We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us! Job Description Position Summary: The Lead AI Security Architect defines and inspires the security architecture strategy for artificial intelligence (AI) and machine learning (ML) systems across the enterprise. You will design the security of AI-enabled platforms, data pipelines, and models with corporate cybersecurity, privacy, and compliance frameworks in mind. You will be an expert, ensuring AI projects meet secure-by-design principles, while mitigating risks associated with generative AI, large language models (LLMs), and autonomous systems. You will balance innovation in AI with risk. You influence secure development of AI systems and ensure responsible adoption of advanced technologies across the enterprise.

Requirements

• Bachelor's Degree or equivalent years of relevant work experience.
• Legal authorization to work in the U.S. We will not sponsor individuals for employment visas, now or in the future, for this job opening.
• Ability to travel up to 10%.
• Technical depth in both cybersecurity and AI domains.
• Ability to translate complex concepts to executives and technical teams both verbally and in writing.
• Expertise in emerging AI security trends and best practices.
• Collaborative and mentoring approach with cross-functional teams.

Nice To Haves

• Typically requires 12+ years of relevant experience in cybersecurity architecture.
• 3+ years focused on AI/ML or data science security.
• Advanced degree in Computer Science, Engineering, Cybersecurity, or related field
• Experience with AI/ML pipelines, MLOps, Model Context Protocol (MPC), Agentic Identity, and cloud-native architectures (AWS SageMaker, Azure ML, GCP Vertex AI).
• Expertise in data protection, identity and access management, encryption, and secure software development.
• Knowledge of AI threat landscapes, adversarial machine learning, and model integrity protection.
• Experience with compliance frameworks such as NIST AI RMF, ISO/IEC 42001, and data privacy regulations (GDPR, CCPA).
• Professional certifications such as CISSP, CISM, CCSP and enterprise architecture certifications.
• AI/ML certifications (e.g., TensorFlow, AWS ML Specialty, Microsoft Azure AI Engineer).
• Hands-on experience with secure LLM deployments and GenAI security testing.
• Experience in OT or industrial AI environments (IEC 62443 knowledge).

Responsibilities

• Develop the enterprise AI security architecture. Align it with our goals, AI governance frameworks (e.g., NIST AI RMF, ISO/IEC 42001), and cybersecurity standards (e.g., NIST CSF, ISO 27001, IEC 62443).
• Define secure architectures for AI/ML model development, deployment, and integration with enterprise data and cloud platforms.
• Establish security reference architectures for GenAI, LLMOps, MLOps, and AI-driven automation.
• Conduct AI threat modeling, risk assessments, and red teaming for AI/ML systems.
• Find and address AI-specific risks such as model inversion, prompt injection, data poisoning, and adversarial attacks.
• Support compliance with the latest AI security and ethics regulations (e.g., EU AI Act, U.S. Executive Orders on AI, sector-specific standards).
• Guide data scientists and developers on implementing secure model training, validation, and inference pipelines.
• Partner with enterprise architects to integrate AI trust controls (authenticity, traceability, explainability, and accountability) into platforms and services.
• Evaluate and deploy AI security tools for model protection, data governance, and AI behavior monitoring.
• Collaborate with product security, DevSecOps, and data engineering teams to embed AI security into the SDLC and CI/CD pipelines.
• Work with legal, risk, and compliance teams to establish AI acceptable use, data residency, and model governance policies.
• Lead security reviews and architecture boards for AI-enabled projects.
• Stay current on AI cybersecurity research, frameworks, and the latest AI threats.
• Develop best practices and strategies for responsible AI security and assurance.
• Mentor junior architects and engineers in AI and cybersecurity principles.

Benefits

• Health Insurance including Medical, Dental and Vision
• 401k
• Paid Time off
• Parental and Caregiver Leave
• Flexible Work Schedule where you will work with your manager to enjoy a work schedule that can be flexible with your personal life.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees