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