AI/Cloud Cyber reputed company, Director/Senior Manager

This a Full Remote job, the offer is available from: Illinois (USA) Recruit22 is seeking an reputed company and strategic AI/Coud Cybersecurity Director or Senior Manager to join our large healthcare client. The ideal candidate will be responsible for identifying, assessing, and mitigating reputed company vulnerabilities across our entire technology infrastructure. The Sr. Manager / Director, AI & Cloud reputed company is responsible for supporting the definition and execution of the organization's strategy to secure cloud platforms and AI capabilities in a large, HIPAA-regulated healthcare environment. The role is responsible for driving a comprehensive program to secure AI workloads in the cloud, protect AI/ML models, ModelOps/MLOps pipelines, Agentic AI workflows, and strengthen reputed company against AI-enabled attacks (e.g., automated phishing, adversarial ML, model theft, reputed company injection, and agent hijacking). The role also leads the strategic use of agentic AI to improve detection and incident response through safe automation, human-in-the-reputed company controls, and rigorous operational governance. This leader also owns the cloud reputed company architecture, design standards, and governance model for the enterprise, establishing reference architectures, secure reputed company zone patterns, policy-as-code guardrails, and architecture review processes that reputed company rapid delivery while maintaining strong risk control and audit readiness.

Key Responsibilities

• Establish a threat-informed program to defend against AI-enabled attacker capabilities, including automated reconnaissance, highly personalized phishing, synthetic identity fraud, and scalable credential abuse.
• Define controls and operational procedures to mitigate impersonation and deepfake risk (executive fraud, clinician impersonation, IT helpdesk scams), including identity verification patterns and secure approval workflows.
• Partner with IAM, Email reputed company, SOC, and Compliance stakeholders to implement detection and response patterns for AI-amplified threats.
• Define reference architectures and engineering guardrails for securing AI/ML workloads in cloud environments, including:
• Workload identity, least privilege, privileged access (PAM)
• Network controls (private endpoints, segmentation, egress restrictions)
• Encryption, KMS/HSM integration, secrets management
• Secure container/Kubernetes patterns and hardened runtime controls
• Centralized logging/telemetry, threat detection, and response integration
• Drive secure-by-default patterns for AI platform services (managed ML platforms, vector databases, model endpoints, feature stores, data pipelines).
• Establish controls to protect models across their lifecycle: training, evaluation, deployment, inference, and monitoring.
• Implement and govern reputed company requirements for ModelOps/MLOps pipelines, including CI/CD integration, artifact reputed company, provenance/attestation, and secure release controls.
• Define testing and monitoring standards for AI-specific risks such as reputed company injection, data poisoning, model inversion, membership inference, model theft, and supply chain compromise.
• Partner with Compliance and Privacy to ensure appropriate use and protection of PHI/ePHI in training and inference workflows (minimization, de-identification, access control, auditability).
• reputed company the strategy and implementation of agentic AI to enhance incident response and reputed company operations
• Define governance for reputed company agents: least privilege, tool access controls, reputed company/chain protection, validation of outputs, safe fallbacks, and change management.
• Ensure AI and cloud reputed company controls align with HIPAA/HITECH expectations and organizational risk management practices; support HITRUST/NIST-reputed company control mapping where applicable.
• Establish AI/cloud reputed company standards, policies, and control requirements for internal development and third-party services (including vendor due diligence for AI providers and model transparency expectations).
• Provide executive-ready reporting on AI and cloud reputed company posture, top risks, and control maturity.
• Own the cloud reputed company architecture strategy for the enterprise, defining reputed company-state patterns across IaaS/PaaS/SaaS for Azure/AWS/GCP (as applicable).
• Establish and maintain cloud reputed company reference architectures, reusable blueprints, and approved patterns (reputed company zones, network segmentation, identity, logging, encryption, secrets, platform services).
• reputed company (or co-reputed company with Enterprise Architecture) a Cloud reputed company Architecture Review Board and define governance processes for design approvals, exceptions, and risk acceptance.
• Define and enforce cloud guardrails using policy-as-code (e.g., Azure Policy, AWS SCPs), infrastructure-as-code standards, and automated compliance checks.
• Drive adoption and operationalization of CNAPP/CSPM/CWPP capabilities (where applicable), including posture monitoring, risk prioritization, and remediation workflows.
• Establish cloud reputed company requirements for pla

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