Senior Kubernetes Platform Engineer AWS GitOps

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