Hybrid Kubernetes Platform Architect for Enterprise AI

Applix; Peoria (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Applix in Peoria, IL seeks a Kubernetes Engineer to design, implement, and maintain production-grade Kubernetes platforms across hybrid environments. You will own the platform foundation for secure, reliable AI workloads with automation, security, and enterprise-scale operations.

You will establish multi-tenant standards, build GitOps-driven operations, and define deployment and observability patterns while embedding security across identity, secrets, policy enforcement, and workload protection.

Qualifications

• Must have production Kubernetes platform experience at scale.
• Hands-on Kubernetes administration, operations, lifecycle management.
• Experience with cloud, on-prem, or hybrid infra.

Responsibilities

• Design, deploy, and operate highly available Kubernetes platforms.
• Establish GitOps-driven platform operations for provisioning, upgrades, and scaling.
• Define secure multi-tenant standards for governance and workload isolation.
• Define platform standards for deployment, observability, and production readiness.
• Implement security controls including RBAC, secrets management, and cluster hardening.
• Troubleshoot Linux, networking, storage architecture, and infra issues.
• Improve platform reliability, incident response, and SLOs.
• Drive automation, performance, and cost-efficiency improvements.

Skills

Kubernetes

Platform engineering

GitOps

Terraform

Helm

Security hardening

Argo CD

OpenTelemetry

Cloud platforms

Linux

Tools

Terraform

Helm

Argo CD

Flux

Kubernetes security tooling

Job description

Applix in Peoria, IL seeks a Kubernetes Engineer to design, implement, and maintain production-grade Kubernetes platforms across hybrid environments. You will own the platform foundation for secure, reliable AI workloads with automation, security, and enterprise-scale operations.

You will establish multi-tenant standards, build GitOps-driven operations, and define deployment and observability patterns while embedding security across identity, secrets, policy enforcement, and workload protection.