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St. Louis, MO, USA
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• Own and evolve the enterprise AI security architecture and strategy, aligning business goals, technology platforms, and risk management practices.
• Assist in defining secure-by-design patterns and standards for AI/ML systems
• Establish and maintain AI-specific security artifacts
• Ensure consistent adoption of NIST AI RMF, MITRE ATLAS, CIS, ISO 27001 across AI initiatives.
• Establish architectural governance and enforce adherence to AI security standards across product teams and platforms.
• Influence AI design decisions early in the lifecycle to reduce downstream risk and rework.
• Partner with enterprise stakeholders to balance speed of innovation with risk tolerance and regulatory expectations.
• Evaluate AI frameworks, agents, vector databases, and third-party AI platforms for security posture and enterprise readiness.• Recommend and rationalize AI security tooling as part of the broader enterprise
security strategy.
• Monitor emerging AI threats, regulatory guidance, and industry best practices to inform security strategy and standards.
What Experience You’ll Need
• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 8–12+ years of experience in cybersecurity engineering or architecture within a complex enterprise environment.
• 2–4+ years of hands-on experience securing or reviewing AI/ML systems and platforms.
• Strong understanding of:
o LLM architectures, embeddings, and Retrieval-Augmented Generation (RAG) patterns
o End-to-end ML pipelines (training → validation → deployment → inference)
o AI model supply chain risks (model registries, containers, dependencies, open-source components)
o Zero Trust and identity-centric security models
o Cloud security across Azure, AWS, and GCP
• Proven ability to influence architecture decisions and lead cross-functional initiatives at the enterprise level.
• Excellent communication skills, with the ability to engage senior technical and business leaders
Bachelor's degree
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