AI DevSecOps Engineer

About the role

An experienced AI DevSecOps Engineer is sought to integrate AI-driven capabilities into DevSecOps practices, strengthen application and infrastructure security and automate CI/CD pipelines. The role uses AI tools to identify vulnerabilities, automate security testing, improve threat detection and embed security controls throughout the software development lifecycle.

Key responsibilities

• Design, implement and maintain secure CI/CD pipelines with integrated security checks and automated compliance controls.
• Integrate AI/ML-based tools into DevSecOps workflows to improve vulnerability detection, threat analysis and security automation.
• Run automated security testing including SAST, DAST, SCA, container security and API security testing.
• Secure cloud environments on AWS, Azure or GCP, covering identity and access management, network security and workload protection.
• Apply IaC security with tools such as Terraform, Checkov or equivalents.
• Use AI-assisted code analysis to find vulnerabilities, misconfigurations and security risks.
• Build automation scripts and workflows in Python, Bash or PowerShell.
• Manage secrets, encryption, access controls and security policies across development and deployment environments.
• Monitor security events, support incident response and remediation, and work with development, platform engineering, cloud and cybersecurity teams.
• Set up security metrics, dashboards and reporting on vulnerabilities, remediation and compliance.
• Evaluate emerging AI security tools and risks around AI-generated code, LLM integrations and AI-enabled applications.

Required profile

• 5+ years of experience in DevOps, DevSecOps, cloud engineering or cybersecurity, with hands-on security automation.
• Strong experience designing and managing CI/CD pipelines.
• Experience with security testing tools such as SonarQube, Snyk, Checkmarx, Veracode, OWASP ZAP, Trivy or equivalents.
• Experience with Docker, Kubernetes, container security and cloud-native application security.
• Cloud security knowledge across AWS, Azure or GCP.
• IaC experience with Terraform, Ansible or CloudFormation and related security scanning.
• Practical experience with AI-powered security tools, AI-assisted code analysis or ML-based security automation.
• Knowledge of OWASP Top 10, secure SDLC, vulnerability management, threat modeling and security compliance.

Required skills

• CI/CD: Jenkins, GitLab CI/CD, GitHub Actions, Azure DevOps or similar.
• Scripting: Python, Bash or similar.
• Security: secrets management, IAM, encryption, security policies, audit logging.