Kubernetes Platform Engineer – Voice Services Modernization

head-huntress.com

Philadelphia, PA

JOB DETAILS
SKILLS
Amazon Web Services (AWS), Ansible, Artificial Intelligence (AI), Automation, Best Practices, Business Operations, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Documentation, GCP (Good Clinical Practices), High Availability, IP Multimedia System (IMS), Identify Issues, Information Technology & Information Systems, Knowledge Transfer, Machine Tool, Microsoft Windows Azure, Middleware, Operational Support, Production Support, Python Programming/Scripting Language, Red Hat Linux Operating System, Reporting Dashboards, Risk, SIP (Session Initiation Protocol), Scripting (Scripting Languages), Software Administration, Splunk, Strategic Planning, System Migration, Systems Administration/Management, Test Automation, Testing, Validation Testing, Virtual Machine (VM), Voice Applications
LOCATION
Philadelphia, PA
POSTED
27 days ago

Experience level: Mid-senior Experience required: 10 Years Education level: Bachelor’s degree Job function: Information Technology Industry: Information Technology and Services Pay rate : $65 per hour Total position: 1 Relocation assistance: No Visa sponsorship eligibility: No End Client: Comcast Please Note: We are only looking for W2 Candidates. 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, 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 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, 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 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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