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Kubernetes Platform Engineer

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Job Description - Kubernetes Platform Engineer

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
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