About the Role
We are looking for an experienced AI DevSecOps Engineer to integrate AI-driven capabilities into DevSecOps practices, strengthen application and infrastructure security, and automate CI/CD pipelines. The ideal candidate will have strong hands-on experience in DevSecOps, cloud security, Infrastructure as Code (IaC), and AI/ML-enabled security automation. This role requires the ability to leverage AI tools to identify vulnerabilities, automate security testing, improve threat detection, and embed security controls throughout the software development lifecycle.
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Key Responsibilities
- Design, implement, and maintain secure CI/CD pipelines with integrated security checks and automated compliance controls.
- Integrate AI/ML-based tools and capabilities into DevSecOps workflows to improve vulnerability detection, threat analysis, and security automation.
- Implement automated security testing, including SAST, DAST, SCA, container security, and API security testing.
- Secure cloud environments across AWS, Azure, or GCP, including identity and access management, network security, and workload protection.
- Implement Infrastructure as Code (IaC) security using tools such as Terraform, Checkov, or equivalent solutions.
- Leverage AI-assisted code analysis and security tools to identify potential vulnerabilities, misconfigurations, and security risks.
- Develop automation scripts and workflows using Python, Bash, or PowerShell.
- Implement secrets management, encryption, access controls, and security policy enforcement across development and deployment environments.
- Monitor security events, analyze threats, and support incident response and remediation activities.
- Work closely with development, platform engineering, cloud, and cybersecurity teams to embed security best practices into the SDLC.
- Establish security metrics, dashboards, and reporting to track vulnerabilities, remediation progress, and compliance.
- Evaluate emerging AI security tools and practices, including risks associated with AI-generated code, LLM integrations, and AI-enabled applications.
Requirements
- 5+ years of experience in DevOps, DevSecOps, cloud engineering, or cybersecurity, with relevant hands-on security automation experience.
- Strong experience designing and managing CI/CD pipelines using Jenkins, GitLab CI/CD, GitHub Actions, Azure DevOps, or similar tools.
- Hands-on experience with security testing tools such as SonarQube, Snyk, Checkmarx, Veracode, OWASP ZAP, Trivy, or equivalent platforms.
- Experience with Docker, Kubernetes, container security, and cloud-native application security.
- Strong understanding of cloud security across AWS, Azure, or GCP.
- Experience with Infrastructure as Code tools such as Terraform, Ansible, or CloudFormation and related security scanning practices.
- Proficiency in Python, Bash, or similar scripting languages for automation.
- Practical experience using AI-powered security tools, AI-assisted code analysis, or ML-based security automation.
- Understanding of OWASP Top 10, secure SDLC, vulnerability management, threat modeling, and security compliance standards.
- Knowledge of secrets management, IAM, encryption, security policies, and audit logging.
- Strong troubleshooting, analytical, and problem-solving skills.
