Red Hat OpenShift Engineer

EngineerEngineerPart TimeRemoteTeam 11-50H1B No SponsorCompany Site LinkedIn

Location

United States

Posted

37 days ago

Salary

Not specified

Professional Certificate5 yrs expEnglishAnsibleAzureCloudGrafanaKubernetesLinuxOpen ShiftPrometheusTerraform

Job Description

• Design, architect, and build a multi-tenant OpenShift cluster on bare metal • Configure and maintain all aspects of the OpenShift platform for high availability, scalability, and security • Define and implement networking, storage, ingress, monitoring, and logging • Develop detailed architecture documents, blueprints, and SOPs • Lead and execute migration of existing workloads from on-premise and Azure environments to OpenShift • Ensure smooth onboarding for multiple AI-focused client tenants with isolated environments • Support DevOps team with advanced Linux/OpenShift troubleshooting • Implement and enforce RBAC, tenant isolation, resource quotas, and compliance controls • Optimize performance for AI-heavy workloads running on GPU-enabled infrastructure • Own operational stability, platform upgrades, and monitoring

Job Requirements

5+ years of deep hands-on experience with Red Hat OpenShift and Kubernetes
Proven experience designing, building, and managing bare metal OpenShift clusters
Solid understanding of Linux internals, container runtimes, networking, and troubleshooting
Experience with application migration from both on-premise and Azure environments into OpenShift
Strong experience with multi-tenancy architecture, including workload isolation and security
Familiarity with storage (CSI), networking (CNI), and service mesh implementations
Proficiency in monitoring and observability tools (e.g., Prometheus, Grafana, ELK)
Experience with Infrastructure as Code (Ansible, Terraform) and CI/CD automation
Strong documentation and communication skills
Certifications (Required) Red Hat Certified Specialist in OpenShift Administration
Red Hat Certified Engineer (RHCE) or equivalent Linux certification
Nice to Have Familiarity with AI/ML compute environments (e.g., GPU workloads, NVIDIA operators)
Experience with hybrid cloud or edge computing models
Exposure to enterprise-grade security, compliance, and policy enforcement