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Niche AI-security role but mid-level, metro location, and known services brand drive moderate competition.
Highly specialized AI/ML security and DevSecOps skills reduce cross-industry transferability.
Explicit 5.5+ years plus mandatory ML security, cloud, IaC, and compliance requirements make filters highly strict.
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Design, implement, and maintain security controls for AI/ML platforms, including LLM-powered applications and unstructured data pipelines.
Conduct threat modeling and mitigate AI security risks such as prompt injection, model inversion, and adversarial attacks.
Embed security in CI/CD pipelines and manage secure cloud infrastructure using Infrastructure as Code, while ensuring regulatory compliance and incident response.
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 IaC.
Strong understanding of cloud platforms (AWS, Azure, GCP) and security best practices including OWASP, Zero Trust, and secrets management solutions.
Bachelor’s or master’s degree in computer science, IT, or related field.
Experienced in securing AI/ML environments with deep knowledge of AI-specific security risks and controls.
Operational expertise in managing secure AI platforms, encompassing both development (CI/CD) and infrastructure (cloud, containers, Kubernetes).
Ability to collaborate effectively with cross-functional teams including AI engineers, DevOps, and security stakeholders to build compliant and scalable AI solutions.