Job Summary
Role SummaryThe 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
Key ResponsibilitiesDefine reference architectures and technical standards for secure AIML adoption (data governance, model lifecycle security, LLMagentic 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, ISOIEC 42001, OWASP LLM Top 10) from a technical architecture perspective.
Skill Requirements
Key ResponsibilitiesDefine reference architectures and technical standards for secure AIML adoption (data governance, model lifecycle security, LLMagentic 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, ISOIEC 42001, OWASP LLM Top 10) from a technical architecture perspective.
Other Requirements
Role SummaryThe 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 ResponsibilitiesDefine reference architectures and technical standards for secure AIML adoption (data governance, model lifecycle security, LLMagentic 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, ISOIEC 42001, OWASP LLM Top 10) from a technical architecture perspective.Required Qualifications8+ years in security architecture or enterprise architecture roles, including recent experience architecting controls for AIML or data platforms.Deep understanding of AIML system design (data pipelines, model trainingserving, MLOps) and associated security and privacy risks.Strong grasp of cloud security architecture (Azure andor AWSGoogle Cloud Platform), identity and access management, network segmentation, and zero-trust principles.Familiarity with AI governance and security frameworks: NIST AI RMF, ISOIEC 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 QualificationsArchitecture certifications (SABSA, TOGAF) andor security certifications (CISSP, CCSP).Experience building AIML platforms or securing generative AIagentic AI deployments at enterprise scale.Retail or large consumer-brand enterprise experience.
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