Senior Kubernetes Platform Engineer – AWS / GitOps

3Core Systems, Inc is an SAP and Success Factors Partner with employees located across the United States. Our organization is dedicated to customer and employee satisfaction. We provide High Quality, Cost efficient and Competitive Solutions and Resources.

3Core Systems is looking for a Senior Kubernetes Platform Engineer AWS GitOps for one of our clients

Job Title: Senior Kubernetes Platform Engineer AWS GitOps

Job Location: Peoria, IL, 61629, Onsite

Shift: M-F, 8am - 5pm

Estimated Duration (In Months): 13

Must Have Skills/Attributes: Automation, AWS, Kubernetes, Security

Experience Desired:

• 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

Job Description

Education Requirements:

Bachelor's degree

Preferred Certification:

• Kubernetes
• CKA
• CKAD
• CKS

Required Skills for the Senior Kubernetes Platform Engineer:

• 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

Senior Kubernetes Platform Engineer Overview:

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

Responsibilities:

• 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