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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Kubernetes Platform Engineer AWS GitOps - **Company:** 3Core Systems, Inc - **Location:** Peoria, AZ, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Artificial Intelligence, Amazon Web Services, Application Release Automation, Microsoft Azure, Cloud Computing, Configuration Management, Cyber Security, Computer Networks, Linux, Key Management, Network Architecture, Octopus Deploy, OpenShift, Role-Based Access Control, Cloud Platform System, Istio, HybridCloud, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Storage Technologies, Rancher, Terraform, Vulnerability Analysis - **Published:** November 12, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-kubernetes-platform-engineer-aws-gitops-peoria-az--88e9513e-f1be-4a41-95ed-6b03da3765c8 ## About the Role Amazon Web Services (AWS), Automation, Amazon Web Services (AWS), Microsoft Windows Azure, Cloud Computing, Security Infrastructure, Identify Issues, Storage Architecture, Linux Operating System, Network Architecture/Engineering, * Kubernetes and Container Platform experience (10 yrs) * Infrastructure Automation - IaC, GitOps (10 yrs), * Enterprise cloud experience with AWS or Azure (10 yrs), * Security and Observability experience (10 yrs) Required Minimum Education: Bachelor's Degree Preferred Certifications/Licenses: Kubernetes, CKA, CKAD, or CKS, Bachelor's degree Preferred Certification: * Kubernetes * CKA * CKAD * CKS, * 10 years of experience * Proven success building and evolving production-grade Kubernetes platforms across cloud, on-premises, or hybrid environments * Demonstrated experience operating Kubernetes at scale, including responsibility for reliability, security, and platform lifecycle management * Deep expertise in Linux, cluster networking, and storage architecture, including the ability to diagnose issues across the infrastructure stack * Hands-on experience with infrastructure as code and release automation in production environments, including Terraform and Helm-based platform delivery * Experience using GitOps tools such as Argo CD or Flux to manage deployments and improve control, consistency, and delivery efficiency in production environments * Strong hands-on Kubernetes security experience, including RBAC, network policies, secrets and key management, admission or policy enforcement, and production cluster hardening in enterprise environments Core Technology Areas: Kubernetes & Container Platform * Kubernetes platform administration, operations, and lifecycle management * Helm-based release and configuration management Infrastructure Automation * Infrastructure as code, automation, and platform provisioning * GitOps-driven deployment and configuration management Cloud & Hybrid * At least one major cloud platform, preferably AWS or Azure * Enterprise cloud and hybrid platform environments Security & Observability * Platform security controls, policy enforcement, and workload protection * Observability, monitoring, and operational readiness practices Preferred Skills: * Experience with enterprise Kubernetes distributions and managed services such as EKS, AKS, GKE, OpenShift, or Rancher * Familiarity with service mesh capabilities that support traffic management, security, and platform resilience * Exposure to modern observability frameworks, including OpenTelemetry, to support scalable monitoring practices * Familiarity with container image security, vulnerability scanning, and software supply chain practices that strengthen overall platform security maturity * Experience supporting enterprise AI platforms, including Accenture AI Refinery ## Description The Senior Kubernetes Platform Engineer is responsible for the design, operation, and continuous improvement of the Kubernetes platform supporting a shared enterprise AI offering aligned to Accenture AI Refinery. This position enables secure, scalable, and well-governed AI workloads by advancing platform reliability, operational maturity, developer enablement, and the controls required to support critical services across cloud and on-premises environments. Position Contributions to the Group: * This position supports the delivery of enterprise AI capabilities through a secure, scalable, and reliable Kubernetes platform * The role is responsible for establishing the platform foundation required to support governed AI workloads across cloud and on-premises environments, with emphasis on operational stability, security, and enterprise scalability * Establish the initial Kubernetes platform foundation across cloud and on-premises environments, including core cluster patterns to support early AI workload onboarding * Implement baseline GitOps, access, security, and operational controls to improve consistency, reduce deployment risk, and support production readiness * Define an operating model for the platform, including support expectations, reliability priorities, and an approach to scale for enterprise AI workloads, * Lead the design, deployment, and lifecycle management of highly available Kubernetes platforms across hybrid environments to ensure resilience, scalability, and operational consistency * 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 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, secrets management, and workload protection practices * Establish observability capabilities that accelerate issue detection, improve incident response, and support data-driven reliability management * Own and improve platform service objectives, operational readiness, and support practices to sustain reliable production operations * Resolve complex platform issues across networking, storage, and runtime layers while driving long-term architectural improvements * Collaborate with application and security teams to standardize deployment patterns, improve reliability, and support platform adoption * Drive continuous improvement in automation, performance, and cost efficiency to increase platform value and reduce operational overhead