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Remote flexibility and recognizable global brand increase competition, but niche AI-security specialization reduces applicant pool.
Role requires specialized AI and multi-cloud security expertise, limiting cross-industry portability.
Multiple mandatory domain-specific skills and senior L3 responsibility create stringent technical filters.
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Own and operate the AI runtime control plane, including inline enforcement pipeline for AI traffic across multi-cloud environments (Azure, AWS, GCP).
Author and tune runtime policies to enforce AI security controls (e.g., prompt injection prevention, PII masking) balancing detection accuracy with minimal false positives.
Lead deep incident investigations as final escalation point, implement closed-loop defenses incorporating adversarial testing findings to update policies and detection logic continuously.
Experience: Significant hands-on engineering responsibility in cloud security (Azure, AWS, GCP) and securing or operating AI/ML or LLM-based systems, including AI security tool deployment and tuning.
Technical skills: Proficiency in KQL, PowerShell, Python; Infrastructure as Code (Terraform); expertise in integrating enterprise security platforms, multi-cloud security engineering, Kubernetes security (AKS/EKS).
Education: Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or equivalent practical experience.
Work conditions: Willingness to work nonstandard hours for incident response, some travel required, flexible remote work available.
Experienced in building and integrating complex AI security runtime and detection systems within multi-cloud enterprise environments.
Skilled in balancing security with low-friction enablement, comfortable operating in a default-allow security culture with fast, precise controls.
Capable of leading L3 security incident response, collaborating across global teams, and translating adversarial/red-team findings into operational security enhancements.