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Mid-level DevSecOps/AI-security role, metro location, and broad skillset increase candidate competition.
Specialized AI security and DevSecOps skills limit transferability across non-AI or non-cloud-native employers.
Explicit 5.5+ years and deep DevSecOps and AI-security tech requirements lead to strict shortlisting.
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Design, implement, and maintain security controls specifically for AI/ML platforms, including LLM-powered applications.
Develop and manage secure AI data pipelines and ensure compliance with data privacy regulations and governance frameworks.
Embed security within CI/CD pipelines and cloud infrastructure using IaC, container security, and observability solutions for AI systems.
5.5+ years of experience in DevOps, DevSecOps, Cloud Infrastructure, or AI/ML Security engineering.
Proficiency in Python and Bash scripting; experience with Terraform or Pulumi for Infrastructure as Code.
Strong knowledge of cloud platforms AWS, Azure, or GCP and related security best practices.
Bachelor’s or master’s degree in computer science, IT, or a related field.
Experienced with AI security threats and mitigations including prompt injection, model inversion, data poisoning, and adversarial attacks.
Skilled in securing AI pipelines, containerized environments (Kubernetes), and integrating security within DevOps workflows.
Familiar with regulatory compliance (GDPR, CCPA, HIPAA) and security frameworks (SOC2, ISO27001, NIST AI RMF).