AI Application Security Engineer

What you'll do

• Embed security guardrails into the Secure SDLC across design, development, testing, and deployment phases.
• Integrate and optimize SAST, DAST, SCA, and secrets scanning tools within CI/CD pipelines.
• Lead threat modeling and secure design reviews for cloud-native and microservices-based applications.
• Manage container and Kubernetes security including image hardening, vulnerability management, and runtime controls.
• Define and enforce API security standards such as authentication, authorization, and rate limiting.
• Triage, prioritize, and remediate security findings in partnership with engineering teams.
• Establish secure coding standards and provide guidance on common vulnerabilities like the OWASP Top 10.
• Enhance software supply chain security through dependency management and build pipeline protections.

What we're looking for

• Bachelor's degree in Computer Science, Information Security, or a related field.
• 6+ years of experience in cybersecurity or cloud security engineering.
• 3+ years of hands-on experience securing GCP, Azure, or AWS environments in production enterprise environments.
• Experience integrating security controls into CI/CD pipelines and Kubernetes environments including container hardening and vulnerability scanning.
• Experience securing AI/ML workloads and Generative AI systems, including model, data, and inference endpoint protection.
• Cybersecurity background and operational experience (preferred).
• Certifications from ISC2 (e.g., CISSP, CCSP) or ISACA (e.g., SSCP, CC, CISA, CISM) (preferred).
• Experience designing and managing IAM, encryption, and network security controls (preferred).