Kubernetes Platform Engineer - Voice Services Modernization

MetaOption, LLC
Philadelphia, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Philadelphia, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Automation of Tests
Azure
Cloud Computing
Cloud Engineering
Computer Programming
Continuous Integration
DevOps
Middleware
Python
Openshift
OpenStack
Ansible
Prometheus
Azure
Datadog
Data Logging
Scripting (Bash/Python/Go/Ruby)
Google Cloud Platform
Cloud Platform System
Grafana
Backend
Containerization
Kubernetes
Infrastructure Automation Frameworks
Low Latency
Deployment Automation
Terraform
Splunk

Job description

The Kubernetes Platform Engineer - Voice Services Modernization is responsible for designing, deploying, automating, and operationalizing cloud-native infrastructure for mission-critical voice applications. This role focuses on transforming traditional VM-based voice middleware and backend services into scalable, resilient Kubernetes-based platforms using modern DevOps, CI/CD, infrastructure-as-code, and observability practices.

The engineer will work across infrastructure, application modernization, automation, and operational support to ensure highly available, low-latency voice services are successfully migrated into production cloud-native environments.

Core Responsibilities

  • 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, Google Cloud Platform, 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

Requirements

Skills: Expert-level Kubernetes administration, deployment, lifecycle management, and troubleshooting, CI/CD pipeline development and automation experience

Experience level: Mid-senior Experience required: 10 Years Education level: Bachelor's degree Please Note: We are only looking for W2 Candidate's!, * 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, Google Cloud Platform, 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

Preferred / Nice-to-Have Skills

  • 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.

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