Job Title:

AI Architect Location :

Bolingbrook, IL (initial remote ok, preference is local profile)

Duration:

12 Month Must have skill:

AI/ML Job Description :

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. Required Qualifications 8+ 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. 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