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