The Principal Cybersecurity Architect is responsible for driving enterprise-wide technology security strategy and providing technical expertise to business areas and project teams with an emphasis on implementation of innovative, leading-edge security technology solutions. The ideal candidate will display: Strategic Leadership, Collaboration, and Accomplishments Proven Track Record of accomplishments and experience leading the design and deployment of AI Architectures (both On-Premise and Public Cloud) and driving and deploying Secure Cloud Adoption on an enterprise scale from Foundational Security Controls to Cloud migrations. Extensive experience migrating from a large scale onprem datacenter to the cloud while maintaining the proper levels of security, compliance and regulatory adherence. Cross-Functional Communication: Bridging gaps between data scientists, engineers, AI Architects, Cloud Architects, Data Protection professionals, legal, and executive teams. Security Evangelism: Promoting secure-by-design principles across AI and Cloud initiatives. Mentorship & Governance: Leading security teams and establishing governance frameworks for AI and Public Cloud adoption. AI-Specific Security Expertise Understanding of AI/ML Risks: Knowledge of adversarial attacks, model poisoning, data drift, and bias. Model Connectivity & Secure Deployment: Leadership experience with connecting User Interfaces to LLMs, Retrieval-Augmented Generation “RAG” solutions, Agent to Agent architecture design, and securing Model Context Protocol “MCP” deployments, both on-premise and in the cloud. AI Lifecycle Security: Securing data pipelines, training environments, inference APIs, and monitoring systems. Enterprise Security Architecture Zero Trust & Identity Management: Designing architectures that enforce least privilege and secure identity across AI and Cloud systems. Cloud & Hybrid Security: Expertise in securing AI workloads across AWS and Azure, and on-prem environments. Experience leading the Secure design of Cloud Foundational Controls across AWS and Azure. Security Design Patterns: Lead architectural requirements and gain consensus on the use of reusable, scalable patterns for secure AI integration. Technical Depth in AI & Cloud Infrastructure API & Data Security: Securing AI APIs, leading design discussions on strategies to protect data within AI solutions, managing data access controls, designing secure MCP solutions and preventing data leakage. AI System Integration: Designing secure integration points between AI systems and enterprise platforms. Public Cloud Integration: Proven track record of driving an Enterprise on Public Cloud Foundational controls and taking a leadership role on Secure Cloud migrations from on-Premise to Public Cloud solutions. Model Usage Procedures: Designed procedures for organization wide governance on the usage/approval of AI Models. Regulatory & Compliance Knowledge Healthcare Regulations: Deep familiarity with HIPAA, NIST and emerging AI and Cloud governance frameworks. Audit & Risk Management: Ability to design systems that meet audit requirements, mitigate compliance risks, and ensuring Public Cloud environments maintain Audit Readiness.
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Job Type
Full-time
Career Level
Principal