Kubernetes Platform Engineer requires: • Voice Services Modernization • 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. • Proven track record leading end-to-end modernization projects that migrated production VM‑based middleware/backend services (preferably voice or other latency‑sensitive apps) into Kubernetes-based production environments — delivered migration planning, staged cutovers, and successful production rollouts. (JD implies senior-level scope; years below.) • Hands‑on experience operating and running production Kubernetes platforms for high‑availability, low‑latency services — delivered platform lifecycle management, troubleshooting/incident response, operational runbooks, and knowledge transfer to operations teams. • Delivered automation and release pipelines that enabled repeatable deployments and infrastructure lifecycle management in production — produced CI/CD pipelines, infrastructure‑as‑code modules, and automation/playbooks to support testing, deployment, and production cutover activities