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Niche AI-security role but metro location and broad cloud/DevSecOps skills increase applicant competition.
Highly domain-specific AI/security skillset with cloud and DevSecOps emphasis limits cross-industry transferability.
Explicit 10-year cybersecurity minimum plus 3-year AI-security requirement and mandatory tooling make filters stringent.
Design and enforce security guardrails for large language models (LLMs) and autonomous AI agents in cloud and user environments to prevent data leaks and malicious prompts.
Configure and maintain security postures and Data Loss Prevention (DLP) policies for AI workloads across AWS and GCP multi-cloud infrastructures.
Integrate automated security scanning into CI/CD pipelines using tools like Harness and secure artifact management with JFrog Artifactory, including developing AI-powered security detection tools.
Minimum 10 years experience in cybersecurity domains (AppSec, Cloud Security, or DevSecOps).
At least 3 years focused on AI/ML security, including LLM vulnerabilities and guardrail frameworks.
Proven experience with AWS and GCP security policies, IAM, and DLP tools.
Experience with CI/CD tools (specifically Harness) and artifact management platforms (Artifactory).
Experienced in securing containerized workloads and Kubernetes environments (network policies, pod security standards) is advantageous.
Proficiency in coding/scripting with Python, Go, or similar for developing AI-driven security tools is preferred.
Holds relevant certifications such as AWS Certified Security, Google Professional Cloud Security Engineer, CISSP, or specialized AI/ML security credentials.