What are the responsibilities and job description for the Kubernetes Platform Engineer - Hybrid position at Calance?
Location:
Philadelphia, PA,
Kubernetes Platform Engineer Voice Services Modernization
Position Summary
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 Required Technical Skills
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.
Philadelphia, PA,
Kubernetes Platform Engineer Voice Services Modernization
Position Summary
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 Required Technical Skills
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.