AI Security Architect

Role: AI Security Architect

Location: Bolingbrook, IL (Remote ok)

Duration: 12+ Months

Note :- Need Only USC-EAD/ E3/TN

Job Summary:

• The AI Architect will define the target-state architecture for securing AI across Ulta Beauty — spanning data, models, platforms, and applications.
• This role sets technical standards and reference architectures that guide how AI is adopted safely at scale, and provides deep technical leadership to the AI Engineer team and cross-functional stakeholders on secure AI design.

Key Responsibilities

• Define reference architectures and technical standards for secure AI/ML adoption (data governance, model lifecycle security, LLM/agentic AI security, network, and identity boundaries).
• Lead security architecture reviews for new AI initiatives, products, and vendor tools, identifying risks and required controls prior to launch.
• Design enterprise patterns for AI guardrails, output validation, human-in-the-loop controls, and least-privilege access for AI agents and services.
• Partner with enterprise architecture, data platform, and infrastructure teams to ensure AI security controls are embedded consistently across on-prem, cloud, and SaaS AI deployments.
• Evaluate emerging AI security threats and technologies, advising leadership on architectural implications and roadmap priorities.
• Mentor the AI Engineer team on secure design practices; provide technical governance over implementation to ensure alignment with architecture standards.
• Contribute to AI governance policy, risk frameworks, and control mapping (NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10) from a technical architecture perspective.

Skill Requirements

Key Responsibilities

• Define reference architectures and technical standards for secure AI/ML adoption (data governance, model lifecycle security, LLM/agentic AI security, network and identity boundaries).
• Lead security architecture reviews for new AI initiatives, products, and vendor tools, identifying risks and required controls prior to launch.
• Design enterprise patterns for AI guardrails, output validation, human-in-the-loop controls, and least-privilege access for AI agents and services.
• Partner with enterprise architecture, data platform, and infrastructure teams to ensure AI security controls are embedded consistently across on-prem, cloud, and SaaS AI deployments.
• Evaluate emerging AI security threats and technologies, advising leadership on architectural implications and roadmap priorities.
• Mentor the AI Engineer team on secure design practices; provide technical governance over implementation to ensure alignment with architecture standards.
• Contribute to AI governance policy, risk frameworks, and control mapping (NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10) from a technical architecture perspective.

Other Requirements

• The AI Architect will define the target-state architecture for securing AI across Ulta Beauty — spanning data, models, platforms, and applications.
• This role sets technical standards and reference architectures that guide how AI is adopted safely at scale, and provides deep technical leadership to the AI Engineer team and cross-functional stakeholders on secure AI design.
• Define reference architectures and technical standards for secure AI/ML adoption (data governance, model lifecycle security, LLM/agentic AI security, network and identity boundaries).
• Lead security architecture reviews for new AI initiatives, products, and vendor tools, identifying risks and required controls prior to launch.
• Design enterprise patterns for AI guardrails, output validation, human-in-the-loop controls, and least-privilege access for AI agents and services.
• Partner with enterprise architecture, data platform, and infrastructure teams to ensure AI security controls are embedded consistently across on-prem, cloud, and SaaS AI deployments.
• Evaluate emerging AI security threats and technologies, advising leadership on architectural implications and roadmap priorities.
• Mentor the AI Engineer team on secure design practices; provide technical governance over implementation to ensure alignment with architecture standards.
• Contribute to AI governance policy, risk frameworks, and control mapping (NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10) from a technical architecture perspective.

Required Qualifications

• 10+ years in security architecture or enterprise architecture roles, including recent experience architecting controls for AI/ML or data platforms. Deep understanding of AI/ML system design (data pipelines, model training/serving, MLOps) and associated security and privacy risks.
• Strong grasp of cloud security architecture (Azure and/or AWS/Google Cloud Platform), identity and access management, network segmentation, and zero-trust principles.
• Familiarity with AI governance and
• security frameworks: NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLM Applications, and applicable data privacy regulation.
• Demonstrated ability to communicate architecture decisions to both engineering teams and executive stakeholders.

Preferred Qualifications

• Architecture certifications (SABSA, TOGAF) and/or security certifications (CISSP, CCSP).
• Experience building AI/ML platforms or securing generative AI/agentic AI deployments at enterprise scale.
• Retail or large consumer-brand enterprise experience.