AI DevSecOps Engineer
Unison Group
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.
The candidate should be capable of leveraging 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 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
