AI DevSecOps Engineer

Unison Group; Muscat; On-site; OMR 20,000 - 40,000; Full time

Job summary

Unison Group is seeking an experienced AI DevSecOps Engineer to integrate AI-driven capabilities into DevSecOps practices, strengthen application and infrastructure security, and automate CI/CD pipelines. The role emphasizes hands-on security automation, cloud security, and IaC security across AWS, Azure, and GCP.

The ideal candidate will leverage AI tools to identify vulnerabilities, automate security testing, improve threat detection, and embed security controls throughout the software

Qualifications

• 5+ years in DevOps/DevSecOps or cybersecurity with hands-on security automation.
• Experience designing and managing CI/CD pipelines with 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 IaC 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.

Responsibilities

• Design 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 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.

Skills

DevSecOps

CI/CD

Cloud security

Scripting

Tools

Jenkins

GitLab CI/CD

GitHub Actions

Azure DevOps

Terraform

Checkov

Docker

Kubernetes

SonarQube

Snyk

OWASP ZAP

Trivy

Checkmarx

Job description

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.

• 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.