{"id":3331928,"url":"https://alion.io/job/unison-group-ai-devsecops-engineer","title":"AI DevSecOps Engineer","company":{"id":448684,"name":"Unison Group","domain":"unisongroup.com","url":"https://alion.io/company/unisongroup","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":71,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Muscat, Oman"],"countries":["OM"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Checkmarx","optional":false},{"name":"Checkov","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"OWASP Top 10","optional":false},{"name":"OWASP ZAP","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"Snyk","optional":false},{"name":"SonarQube","optional":false},{"name":"Terraform","optional":false},{"name":"Threat Modeling","optional":false},{"name":"Trivy","optional":false},{"name":"Veracode","optional":false}],"status":"live","first_seen_at":"2026-10-27T12:22:30Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-29T22:43:17Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"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.\nThe 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.\nKey Responsibilities\nDesign, implement, and maintain secure CI/CD pipelines with integrated security checks and automated compliance controls.\nIntegrate AI/ML-based tools and capabilities into DevSecOps workflows to improve vulnerability detection, threat analysis, and security automation.\nImplement automated security testing, including SAST, DAST, SCA, container security, and API security testing.\nSecure cloud environments across AWS, Azure, or GCP, including identity and access management, network security, and workload protection.\nImplement Infrastructure as Code (IaC) security using tools such as Terraform, Checkov, or equivalent solutions.\nLeverage AI-assisted code analysis and security tools to identify potential vulnerabilities, misconfigurations, and security risks.\nDevelop automation scripts and workflows using Python, Bash, or PowerShell.\nImplement secrets management, encryption, access controls, and security policy enforcement across development and deployment environments.\nMonitor security events, analyze threats, and support incident response and remediation activities.\nWork closely with development, platform engineering, cloud, and cybersecurity teams to embed security best practices into the SDLC.\nEstablish security metrics, dashboards, and reporting to track vulnerabilities, remediation progress, and compliance.\nEvaluate emerging AI security tools and practices, including risks associated with AI-generated code, LLM integrations, and AI-enabled applications.\nRequirements\n5+ years of experience in DevOps, DevSecOps, cloud engineering, or cybersecurity, with relevant hands-on security automation experience.\nStrong experience designing and managing CI/CD pipelines using Jenkins, GitLab CI/CD, GitHub Actions, Azure DevOps, or similar tools.\nHands-on experience with security testing tools such as SonarQube, Snyk, Checkmarx, Veracode, OWASP ZAP, Trivy, or equivalent platforms.\nExperience with Docker, Kubernetes, container security, and cloud-native application security.\nStrong understanding of cloud security across AWS, Azure, or GCP.\nExperience with Infrastructure as Code tools such as Terraform, Ansible, or CloudFormation and related security scanning practices.\nProficiency in Python, Bash, or similar scripting languages for automation.\nPractical experience using AI-powered security tools, AI-assisted code analysis, or ML-based security automation.\nUnderstanding of OWASP Top 10, secure SDLC, vulnerability management, threat modeling, and security compliance standards.\nKnowledge of secrets management, IAM, encryption, security policies, and 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