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# (1120620) Senior Kubernetes Platform Engineer

- **Company:** DIVERSIFIED INC
- **Location:** Peoria, IL, United States
- **Experience:** Expert
- **Salary:** $115,000 - $120,000
- **Contract:** Permanent contract
- **Skills:** Kubernetes Security, Artificial Intelligence, Amazon Web Services, Application Release Automation, Microsoft Azure, Cloud Computing, Computer Networks, Linux, Disaster Recovery, Key Management, Octopus Deploy, OpenShift, Role-Based Access Control, Service Pack, Software Deployment, Cloud Platform System, Istio, System Availability, AI Platforms, Kubernetes, Storage Technologies, Rancher, Data Analytics, Terraform, Vulnerability Analysis
- **Published:** November 11, 2026
- **Apply:** https://www.careerbuilder.com/job-details/-1120620-senior-kubernetes-platform-engineer-peoria-il--4d2ce76f-5ab8-4105-94ba-2b0db59af57d

## About the Role

Artificial Intelligence (AI), High Availability, Cloud Computing, Energy Efficiency, Software Patches, Risk Management, Operational Improvement, Standards Development, Incident Response, Operational Support, * Bachelor's degree and 10+ years of relevant experience.

 * Proven success building, evolving, and operating production-grade Kubernetes platforms at scale across cloud, on-premises, or hybrid environments, including responsibility for reliability, security, and platform lifecycle management.
 * Deep expertise in Linux, cluster networking, and storage architecture, with the ability to diagnose issues across the full infrastructure stack.
 * Hands-on experience with infrastructure as code and release automation in production, including Terraform and Helm-based platform delivery.
 * Experience managing production deployments with GitOps tools such as Argo CD or Flux.
 * Strong hands-on Kubernetes security experience, including RBAC, network policies, secrets and key management, admission/policy enforcement, and production cluster hardening in enterprise environments.
 * Experience with at least one major cloud platform, preferably AWS or Azure.
 * Experience implementing monitoring, observability, and operational readiness practices., * Experience with enterprise Kubernetes distributions and managed services such as EKS, AKS, GKE, OpenShift, or Rancher.
 * Familiarity with service mesh capabilities for traffic management, security, and platform resilience.
 * Exposure to modern observability frameworks, including OpenTelemetry.
 * Familiarity with container image security, vulnerability scanning, and software supply chain practices.
 * Experience supporting enterprise AI platforms, such as Accenture AI Refinery.
 * Kubernetes certifications such as CKA, CKAD, or CKS.

## Description

* Lead the design, deployment, and lifecycle management of highly available Kubernetes platforms across cloud, on-premises, and hybrid environments, establishing the foundational cluster patterns needed to onboard enterprise AI workloads.
 * Establish secure multi-tenant platform standards that strengthen governance, resource efficiency, and workload isolation across teams.
 * Build automated, GitOps-driven platform operations for provisioning, upgrades, patching, scaling, and decommissioning to reduce deployment risk and improve delivery speed.
 * Define platform standards for deployment, observability, and service operations that improve consistency and reduce engineering friction.
 * Embed security and compliance controls into the platform through policy, identity and access, secrets management, and workload protection practices.
 * Establish observability capabilities that accelerate issue detection, improve incident response, and support data-driven reliability management.
 * Define and own the platform operating model, including service objectives, support expectations, operational readiness, and the approach to scaling for enterprise AI workloads.
 * Resolve complex platform issues across networking, storage, and runtime layers while driving long-term architectural improvements.
 * Drive continuous improvement in automation, performance, and cost efficiency to increase platform value and reduce operational overhead.

Team Collaboration & Work Environment

 * Work within an AI Center of Excellence alongside platform and application developers.
 * Partner with security, infrastructure, and application teams to align technical decisions with enterprise requirements, standardize deployment patterns, and support platform adoption.
 * Collaborate with globally distributed engineering and platform teams to deliver a shared enterprise Kubernetes platform across time zones.
 * Participate in on-call rotation, maintenance readiness, and disaster recovery preparedness.