Sr Specialist System Engineering - DevOps Engineer — AI & Pipeline Automation
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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain Azure DevOps CI/CD pipelines supporting 5G NF application deployment across environments with secure, automated workflows.
Develop AI-assisted pipeline automation capabilities using LLMs for build failure analysis, root-cause diagnosis, and self-healing pipeline workflows.
Lead integration and operational support for Kubernetes-based deployments, MCP servers, and AI-callable automation tools interfacing with Azure and DevOps resources.
Minimum Requirements
Expert-level Linux skills with strong scripting in Bash, Python, and/or PowerShell.
Proven experience building Azure DevOps pipelines using YAML, with knowledge of Azure resources, JSON/YAML, and Azure CLI.
Hands-on experience with Kubernetes (preferably AKS) deployments, troubleshooting, and container orchestration.
Degree: Minimum bachelor’s in Computer Science, Electronics & Communication, Engineering, IT, or related field (preferred). Work Experience Required: Not explicitly mentioned in the JD. Location: Must work offshore from Bangalore with U.S. collaboration hours.
Ideal Candidate Profile
Proven ability to design and maintain enterprise-grade Azure DevOps pipelines with reusable templates, environment gates, approvals, and release workflows.
Experience integrating AI/LLM capabilities into DevOps automation for failure analysis and remediation.
Strong Kubernetes operational knowledge including Helm charts, RBAC, secure service accounts, and pipeline integration.