Senior DevSecOps Engineer - Azure AI Pipelines

What Success Looks Like In This Role

• Provide DevSecOps engineering support for AI projects, incorporating modern cloud-native and AI-driven architectures.
• Design, implement, and manage automated infrastructure provisioning and configuration management solutions, primarily within cloud platforms (e.g., Azure), including environment setup, access provisioning, and resource orchestration.
• Develop, maintain, and optimize robust CI/CD pipelines to automate build, test, and deployment processes, supporting AI/ML workloads.
• Automate test case development and regression testing, including the creation, maintenance, and expansion of automated test suites to ensure quality across ongoing and future releases, with particular focus on AI-based solutions.
• Support the deployment, scaling, monitoring, and lifecycle management of containerized applications, ensuring reliability, performance, and efficient resource utilization.
• Manage and document deployment pipelines and release processes, including both manual and automated workflows, and contribute to the adoption and migration toward modern DevOps platforms (e.g., Azure DevOps, Jenkins).
• Collaborate with cross-functional teams to troubleshoot environment, networking, and access issues, including firewall configuration, port management, and secure connectivity within cloud environments.
• Implement and maintain monitoring and observability solutions to track system performance, analyze trends, and detect anomalies, including configuring alerting mechanisms for proactive issue resolution.
• Identify performance bottlenecks and optimize system components (e.g., databases, application services, networking infrastructure) to improve efficiency, scalability, and responsiveness.
• Support code lifecycle management and DevSecOps strategy development, including version control practices, branching strategies, and release governance for both application and infrastructure code.
• Develop and enhance automation scripts and processes for environment management, data handling, and deployment operations, including environment resets and workflow standardization.
• Maintain comprehensive technical documentation related to environments, deployment processes, automation, and AI integration to support operational continuity and onboarding.
• Facilitate onboarding of team members by providing access, documentation, and guidance on environment setup, tools, and best practices.
• Collaborate with security teams to integrate security practices into development and deployment pipelines, including vulnerability scanning, access control, and compliance with enterprise and industry standards.
• Apply artificial intelligence (AI) techniques and tooling to enhance DevSecOps practices, including improving automated testing, anomaly detection, operational insights, and pipeline optimization.

• Minimum 5 years of experience OR equivalent combination of education and experience.
• Experience with DevOps tools (Jenkins, Azure DevOps,Terraform,Docker, etc.)
• Strong scripting and automation skills (e.g., Python, PowerShell, Bash)
• Strong knowledge of GPU-based systems and CUDA kernels, along with experience in deploying machine learning models with versioning using DVC.
• Hands-on experience with cloud environments, especially Microsoft Azure
• Familiarity with environment provisioning, access management, and deployment best practices for AI projects
• Excellent documentation and communication skills
• Experience onboarding and supporting technical teams

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