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Location: Chicago, IL (Hybrid)
Employment Type: Contract with potential to convert to Full-Time - W2 Only
Role Overview
Reporting to the Director of IT, this Senior Systems Engineer will play a lead role in architecting, deploying, and managing enterprise-grade Kubernetes environments across AWS and GCP. The ideal candidate will be an expert in Kubernetes administration and cloud-native system design, with deep hands-on experience in platform automation, CI/CD pipelines, and service mesh technologies such as Istio. This role is critical in ensuring reliability, scalability, and performance of cloud-based infrastructure supporting critical applications.
Employee Value Proposition
Purpose: This role enables the organization to modernize and future-proof its infrastructure by driving the design and automation of Kubernetes platforms in multi-cloud environments. Your work will directly impact platform resilience, scalability, and developer productivity.
Growth: As a technical SME, you will gain exposure to cutting-edge cloud-native tools and multi-cloud strategies, positioning yourself as a leader in the evolving field of platform engineering. There is a clear path for this contract position to transition into a full-time role based on performance.
Motivators: You will be empowered to lead platform innovation, evaluate and integrate emerging tools, and build solutions that automate and streamline deployment and monitoring. Your contributions will shape a mission-critical foundation for development teams and business growth.
Major Objectives
Design and Deploy Production-Grade Kubernetes Clusters in AWS and GCP
Establish a CI/CD Pipeline and GitOps Deployment Workflow
Lead Platform Automation and Observability Enhancements
Critical Subtasks
Evaluate the Current Cloud Footprint and K8s Infrastructure
Harden Kubernetes Cluster Security and Networking
Integrate and Manage Istio Service Mesh
Provide Technical Leadership and SME Support to Development Teams
Support Multi-Cloud Deployment Readiness and Testing
Drive Continuous Improvements in Deployment Velocity and System Uptime
Continuously Evaluate and Integrate AI to Improve Performance
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