Join a forward-thinking organization driving enterprise-wide AI transformation through a modern AI and Data Analytics platform. As a DevSecOps Engineer, you will play a critical role in building secure, automated, and scalable software delivery pipelines while integrating Generative AI into the development lifecycle. You will work alongside platform engineering, cybersecurity, and IT teams to ensure security is embedded throughout the software development process.

Key Responsibilities

• Design, build, and maintain secure CI/CD pipelines to automate application build, testing, and deployment processes.
• Integrate Generative AI tools into the software development lifecycle to improve developer productivity and code quality.
• Implement security-by-design practices across development, testing, release, and deployment workflows.
• Automate secrets management, vulnerability scanning, policy enforcement, and compliance validation within CI/CD pipelines.
• Manage secure artifact repositories and container registries while ensuring platform integrity and governance.
• Collaborate with Platform Engineering, Cybersecurity, and IT teams to deliver secure, scalable, and reliable deployment processes.
• Support security compliance, governance initiatives, audit activities, and operational readiness for enterprise platforms.
• Provide DevSecOps best practices, security guidance, and contribute to incident response, monitoring, and deployment automation.

Key Requirements

• Bachelor's Degree in Computer Science, Information Security, Engineering, or a related discipline.
• 1–3 years of experience in DevOps, Cloud Engineering, or Cybersecurity, with at least 1 year focused on DevSecOps.
• Hands-on experience with CI/CD platforms such as GitLab, Azure DevOps, Atlassian, or similar DevOps toolchains.
• Good understanding of cloud security, networking, identity and access management, and hybrid cloud environments.
• Experience with secure software development lifecycle (SSDLC), DevSecOps practices, and application security principles.
• Exposure to Generative AI developer tools (e.g., GitHub Copilot) and AI-assisted software development workflows.
• Strong problem-solving, analytical, communication, and stakeholder management skills.
• Self-driven individual with the ability to work collaboratively in a fast-paced, agile environment.

Originally posted on Himalayas

Join a forward-thinking organization driving enterprise-wide AI transformation through a modern AI and Data Analytics platform. As a DevSecOps Engineer, you will play a critical role in building secure, automated, and scalable software delivery pipelines while integrating Generative AI into the development lifecycle. You will work alongside platform engineering, cybersecurity, and IT teams to ensure security is embedded throughout the software development process.

Key Responsibilities

• Design, build, and maintain secure CI/CD pipelines to automate application build, testing, and deployment processes.
• Integrate Generative AI tools into the software development lifecycle to improve developer productivity and code quality.
• Implement security-by-design practices across development, testing, release, and deployment workflows.
• Automate secrets management, vulnerability scanning, policy enforcement, and compliance validation within CI/CD pipelines.
• Manage secure artifact repositories and container registries while ensuring platform integrity and governance.
• Collaborate with Platform Engineering, Cybersecurity, and IT teams to deliver secure, scalable, and reliable deployment processes.
• Support security compliance, governance initiatives, audit activities, and operational readiness for enterprise platforms.
• Provide DevSecOps best practices, security guidance, and contribute to incident response, monitoring, and deployment automation.

Key Requirements

• Bachelor's Degree in Computer Science, Information Security, Engineering, or a related discipline.
• 1–3 years of experience in DevOps, Cloud Engineering, or Cybersecurity, with at least 1 year focused on DevSecOps.
• Hands-on experience with CI/CD platforms such as GitLab, Azure DevOps, Atlassian, or similar DevOps toolchains.
• Good understanding of cloud security, networking, identity and access management, and hybrid cloud environments.
• Experience with secure software development lifecycle (SSDLC), DevSecOps practices, and application security principles.
• Exposure to Generative AI developer tools (e.g., GitHub Copilot) and AI-assisted software development workflows.
• Strong problem-solving, analytical, communication, and stakeholder management skills.
• Self-driven individual with the ability to work collaboratively in a fast-paced, agile environment.

Originally posted on Himalayas