Company Description
Applix provides the industry's only Manufacturing Operating System, designed to deliver unparalleled automation, precision, and scalability to factories. By integrating advanced technologies, Applix empowers manufacturers to optimize production processes and achieve greater control over operations. Our innovative solutions drive smarter, more efficient factories. Join Applix to contribute to the future of intelligent manufacturing.
Role Description
We are seeking a Kubernetes Engineer for a full-time, on-site role based in Peoria, IL. In this role, you will design, implement, and maintain Kubernetes-based infrastructure to support production systems. This is a hands-on platform engineering role for someone who has built and operated production-grade Kubernetes environments across cloud, on-prem, or hybrid infrastructure. You’ll own the platform foundation for secure, reliable, and governed AI workloads — with a focus on automation, reliability, security, developer enablement, and enterprise-scale operations.
What you’ll do
You will lead the design, deployment, and lifecycle management of highly available Kubernetes platforms across hybrid environments, ensuring resilience, scalability, and operational consistency.
You’ll establish secure multi-tenant platform standards, build GitOps-driven operations, define deployment and observability patterns, and embed security controls across identity, secrets, policy enforcement, and workload protection.
You’ll also work closely with application, security, infrastructure, and platform teams to standardize deployment patterns, improve reliability, and support adoption of the enterprise AI platform.
Key responsibilities
- Design, deploy, and operate highly available Kubernetes platforms across cloud and on-prem environments
- Build automated, GitOps-driven platform operations for provisioning, upgrades, patching, scaling, and decommissioning
- Establish secure multi-tenant standards for governance, workload isolation, and resource efficiency
- Define platform standards for deployment, observability, service operations, and production readiness
- Implement Kubernetes security controls including RBAC, network policies, secrets management, policy enforcement, and cluster hardening
- Troubleshoot complex issues across Linux, networking, storage, runtime, and Kubernetes layers
- Improve platform reliability, incident response, operational readiness, and service objectives
- Drive continuous improvement in automation, performance, and cost efficiency
Must-have experience
- Proven experience building and operating production Kubernetes platforms at scale
- Strong hands-on Kubernetes administration, operations, and lifecycle management experience
- Deep understanding of Linux, cluster networking, storage architecture, and infrastructure troubleshooting
- Experience with Terraform, Helm, and infrastructure automation in production environments
- Hands-on GitOps experience with Argo CD, Flux, or similar tools
- Strong Kubernetes security experience, including RBAC, network policies, secrets/key management, admission control, policy enforcement, and production hardening
- Experience with at least one major cloud platform, preferably AWS or Azure
- Experience with EKS, AKS, GKE, OpenShift, Rancher, or similar enterprise Kubernetes platforms
- Familiarity with service mesh, OpenTelemetry, observability frameworks, and container security tooling
- Experience supporting enterprise AI platforms or AI/ML infrastructure
- Certifications such as CKA, CKAD, or CKS are preferred
Initial focus
In the first phase, you’ll help establish the Kubernetes platform foundation across cloud and on-prem environments, implement baseline GitOps, security, access, and operational controls, and define the operating model required to scale governed enterprise AI workloads.
This is a high-impact role for someone who wants to build the platform layer behind enterprise AI adoption — not just maintain clusters.
