Kubernetes Platform Engineer

*Assess existing voice applications, infrastructure dependencies, and VM-based deployment environments

*Design Kubernetes-based architectures optimized for latency-sensitive and high-availability voice workloads

*Containerize middleware and backend applications and establish scalable deployment strategies

*Build and maintain CI/CD pipelines for automated testing, deployment, and lifecycle management

*Develop infrastructure automation using Ansible and Terraform

Deploy, configure, and support Kubernetes and cloud platforms across AWS, Azure, GCP, OpenStack, or OpenShift

*Implement observability solutions including centralized logging, monitoring, alerting, and dashboarding

*Apply operational best practices for security, resiliency, scalability, and production support

*Support staged migration planning, testing validation, and production cutover activities

*Troubleshoot application, platform, and infrastructure issues across cloud-native environments

*Create operational documentation and provide knowledge transfer to engineering and operations teams

*Collaborate with development, operations, and architecture teams to modernize legacy voice services

*Expert-level Kubernetes administration, deployment, lifecycle management, and troubleshooting

*Strong Ansible experience including role and playbook development

*CI/CD pipeline development and automation experience

*Cloud platform administration (AWS, Azure, GCP, OpenStack)

*Infrastructure-as-Code using Terraform

*Experience with monitoring, logging, dashboarding, and alerting platforms

*Scripting or programming experience (Python preferred)

*Production applications support and operational troubleshooting

*Understanding of high-availability and low-latency application architectures

Red Hat OpenShift experience

*AI/ML platform exposure or AI-assisted operations tooling

*Telecom or voice application experience (SIP, SBCs, IMS, voice middleware)

*Experience supporting cloud-native migrations from VM environments

*GitOps and modern deployment methodologies

*Experience with observability platforms such as Prometheus, Grafana, ELK, Splunk, or Datadog

*Outcome / Business Objective

*Deliver a production-ready, Kubernetes-based runtime environment for voice middleware and backend services that improves scalability, resilience, automation, and operational efficiency while minimizing service disruption and migration risk.