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:
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
