Note: The job is a remote job and is open to candidates in USA. Avaya is an enterprise software leader that helps the world’s largest organizations and government agencies forge unbreakable connections. They are seeking a Senior DevOps Engineer to serve as the technical liaison between Cloud Operations and Engineering, focusing on the deployment and release infrastructure. The role involves complex problem-solving, debugging, and maintaining high availability of deployment tooling within CI/CD pipelines.

Responsibilities

• Autonomous Problem Solving: Own and resolve complex technical issues within the CI/CD pipeline and cloud infrastructure without escalating to engineering
• First-Response Debugging: Lead investigations into failed upgrades and orders, identifying root causes in Jenkins, GitHub, and Terraform configurations
• Infrastructure Reliability: Maintain and optimize deployment tooling to ensure high availability and seamless release cycles
• Privileged Troubleshooting: Utilize elevated system access to perform deep-level debugging across Windows and Linux environments as well as CI/CD, version control, and cloud orchestration tools
• Process Improvement: Identify recurring failure patterns in the new order and release process, document, and suggest permanent fixes to Engineering via JIRA

Skills

• Approximately 5 years of hands-on experience in DevOps, SRE, or Tooling Engineering
• Deep understanding of AKS, Kubernetes and Argo CD
• Advanced proficiency in Terraform
• Extensive experience with Jenkins pipelines and GitHub
• Strong troubleshooting skills in both Windows and Linux environments via CLI
• Experience managing secrets and sensitive configurations within a high-access environment
• Proficiency in Python, Bash or similar scripting language to automate 'self-healing' scripts for common pipeline failures and enhance/automate common intra-team tasks
• CKA (Certified Kubernetes Administrator) or HashiCorp Terraform Associate
• Familiarity with observability tools (e.g., Prometheus, Grafana, or ELK stack) to preemptively identify upgrade bottlenecks

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