AI/Cloud Cyber Security, Senior Manager/Architect/Lead

Recruit22 is seeking a seasoned AI & Cloud Cybersecurity leader to drive enterprise security strategy across cloud platforms, AI/ML systems, and emerging agentic AI capabilities. This role leads the design, implementation, and governance of security controls that protect clinical, operational, and AI workloads in a large healthcare organization.

Responsibilities:

• Build a threat‐informed program to counter AI‐enabled attacks (automated phishing, adversarial ML, model theft, prompt injection)
• Define controls to mitigate deepfake, impersonation, and synthetic identity risks
• Partner with IAM, SOC, Email Security, and Compliance to detect and respond to AI‐driven threats
• Establish secure architectures and guardrails for AI/ML workloads: identity, network segmentation, encryption, secrets management, telemetry, and runtime hardening
• Protect models across training, deployment, and inference
• Govern ModelOps/MLOps pipelines (provenance, attestation, CI/CD, secure release gates)
• Define standards for testing AI risks (data poisoning, model inversion, membership inference)
• Lead the adoption of agentic AI for detection and incident response
• Define governance for AI agents: least privilege, tool access, validation, safe fallbacks, and operational controls
• Own cloud security strategy and reference architectures across Azure/AWS/GCP
• Establish secure landing zones, network patterns, encryption/key management, and logging standards
• Lead cloud architecture review processes, exceptions, and risk governance
• Define policy-as-code guardrails (Azure Policy, AWS SCPs) and drive CNAPP/CSPM/CWPP adoption
• Ensure alignment with HIPAA/HITECH, HITRUST, and NIST frameworks
• Set enterprise AI/cloud security standards and requirements for internal teams and vendors
• Provide executive‐level reporting on risk, maturity, and investment priorities

Requirements:

• 10 –15+ years in cybersecurity with deep expertise in cloud security engineering and architecture
• Proven experience building cloud security governance, reference architectures, and automated guardrails
• Hands-on experience securing AI/ML workloads in production: model security, pipeline governance, runtime protection, AI threat testing, and telemetry
• Strong operational background integrating cloud + AI security signals into SIEM/SOAR
• Ability to translate complex AI/cloud risks into business and patient-safety impacts
• Excellent executive communication and leadership skills