We are seeking an experienced Kubernetes Platform Architect to design, govern, and evolve enterprise-grade Kubernetes platforms that support modern cloud-native and AI-enabled workloads. The successful candidate will be responsible for the architecture, security, scalability, automation, and operational excellence of Kubernetes environments across hybrid and multi-cloud landscapes.
This role requires deep expertise in Kubernetes architecture, Linux, container technologies, networking, platform engineering, and cloud-native ecosystem tools, with a strong preference for experience in Azure & Elastic Kubernetes Service (AKS & EKS) and the SUSE Rancher ecosystem.
The architect will work closely with infrastructure, cloud, security, application, DevOps, and AI engineering teams to establish scalable platform standards and enable reliable deployment of business-critical and AI-driven applicationn
Responsibilities
Architecture and Standards
- Design and maintain enterprise Kubernetes platform architectures
- Define platform standards, governance, best practices, and reference architectures.
- Architect highly available, scalable, and secure Kubernetes clusters.
- Lead platform modernization initiatives from traditional infrastructure to cloud-native environments.
- Develop platform roadmaps aligned with business, security, and operational objectives.
Container Platform Design
- Design and support containerized application platforms using Docker and Kubernetes.
- Establish container image management, lifecycle, and deployment practices.
- Drive container adoption strategies and platform engineering initiatives.
Rancher Ecosystem Architecture
- Design and manage solutions leveraging Rancher, Longhorn, Fleet, Harbor
- Develop multi-cluster management strategies.
- Define governance and operational models for large-scale Kubernetes estates.
Networking & Storage Architecture
- Design Kubernetes networking solutions and standards.
- Architect cluster connectivity, traffic flows, and network segmentation.
- Experience with Cilium, kube-vip, MetalLB, NGINX Ingress, Traefik.
- Design persistent storage solutions for Kubernetes environments.
Workload and Application Architecture
- Provide architecture guidance for Stateless applications, Stateful applications, Microservices platforms, Data platforms, AI workloads
- Design appropriate use of Pods, Deployments, StatefulSets, DaemonSets
- Define deployment patterns and workload placement strategies.
DevOps, GitOps & Platform Automation
- Define CI/CD architecture patterns for Kubernetes.
- Implement GitOps operating models.
- Standardize deployment automation using ArgoCD, Flux, Jenkins, Azure DevOps, GitLab CI/CD
- Develop platform deployment standards using Helm.
- Drive Infrastructure-as-Code and platform automation practices.
Security Architecture
- Define and implement enterprise Kubernetes security controls
Monitoring, Observability & Reliability
- Establish enterprise observability architecture.
- Design monitoring and alerting frameworks
- Define centralized logging solutions
- Establish observability standards
Performance & Scalability
- Design platform capacity and scaling strategies.
- Conduct platform optimization and performance reviews.
Cloud & Platform Experience
- Strong experience designing and governing AKS & EKS architectures.
AI Platform Enablement
- Support emerging AI and machine learning workloads by:
- Designing Kubernetes platforms for AI inference and ML workloads.
- Supporting GPU-enabled Kubernetes clusters.
- Defining scheduling and resource allocation patterns for AI workloads.
- Supporting deployment and monitoring of AI inference services.
- Collaborating with AI engineering teams to optimize platform performance and reliability.
Education/Experience/Skills
- 8+ years of infrastructure, cloud, platform engineering, or systems architecture experience.
- 5+ years of hands-on Kubernetes experience in enterprise environments.
- Proven experience defining and applying architecture standards, patterns, and reusable components in complex environments.
- Strong Linux administration and troubleshooting skills.
- Extensive Docker and container runtime experience.
- Strong understanding of networking fundamentals.
- Strong communication skills with the ability to explain design choices and trade-offs to both technical and non-technical stakeholders.
- Collaborative working style, comfortable facilitating cross team discussions and design workshops.
- Self-driven, structured, and able to balance long term architectural direction with hands on design review and support.
We are seeking an experienced Kubernetes Platform Architect to design, govern, and evolve enterprise-grade Kubernetes platforms that support modern cloud-native and AI-enabled workloads. The successful candidate will be responsible for the architecture, security, scalability, automation, and operational excellence of Kubernetes environments across hybrid and multi-cloud landscapes.
This role requires deep expertise in Kubernetes architecture, Linux, container technologies, networking, platform engineering, and cloud-native ecosystem tools, with a strong preference for experience in Azure & Elastic Kubernetes Service (AKS & EKS) and the SUSE Rancher ecosystem.
The architect will work closely with infrastructure, cloud, security, application, DevOps, and AI engineering teams to establish scalable platform standards and enable reliable deployment of business-critical and AI-driven applicationn
Responsibilities
Architecture and Standards
- Design and maintain enterprise Kubernetes platform architectures
- Define platform standards, governance, best practices, and reference architectures.
- Architect highly available, scalable, and secure Kubernetes clusters.
- Lead platform modernization initiatives from traditional infrastructure to cloud-native environments.
- Develop platform roadmaps aligned with business, security, and operational objectives.
Container Platform Design
- Design and support containerized application platforms using Docker and Kubernetes.
- Establish container image management, lifecycle, and deployment practices.
- Drive container adoption strategies and platform engineering initiatives.
Rancher Ecosystem Architecture
- Design and manage solutions leveraging Rancher, Longhorn, Fleet, Harbor
- Develop multi-cluster management strategies.
- Define governance and operational models for large-scale Kubernetes estates.
Networking & Storage Architecture
- Design Kubernetes networking solutions and standards.
- Architect cluster connectivity, traffic flows, and network segmentation.
- Experience with Cilium, kube-vip, MetalLB, NGINX Ingress, Traefik.
- Design persistent storage solutions for Kubernetes environments.
Workload and Application Architecture
- Provide architecture guidance for Stateless applications, Stateful applications, Microservices platforms, Data platforms, AI workloads
- Design appropriate use of Pods, Deployments, StatefulSets, DaemonSets
- Define deployment patterns and workload placement strategies.
DevOps, GitOps & Platform Automation
- Define CI/CD architecture patterns for Kubernetes.
- Implement GitOps operating models.
- Standardize deployment automation using ArgoCD, Flux, Jenkins, Azure DevOps, GitLab CI/CD
- Develop platform deployment standards using Helm.
- Drive Infrastructure-as-Code and platform automation practices.
Security Architecture
- Define and implement enterprise Kubernetes security controls
Monitoring, Observability & Reliability
- Establish enterprise observability architecture.
- Design monitoring and alerting frameworks
- Define centralized logging solutions
- Establish observability standards
Performance & Scalability
- Design platform capacity and scaling strategies.
- Conduct platform optimization and performance reviews.
Cloud & Platform Experience
- Strong experience designing and governing AKS & EKS architectures.
AI Platform Enablement
- Support emerging AI and machine learning workloads by:
- Designing Kubernetes platforms for AI inference and ML workloads.
- Supporting GPU-enabled Kubernetes clusters.
- Defining scheduling and resource allocation patterns for AI workloads.
- Supporting deployment and monitoring of AI inference services.
- Collaborating with AI engineering teams to optimize platform performance and reliability.
Education/Experience/Skills
- 8+ years of infrastructure, cloud, platform engineering, or systems architecture experience.
- 5+ years of hands-on Kubernetes experience in enterprise environments.
- Proven experience defining and applying architecture standards, patterns, and reusable components in complex environments.
- Strong Linux administration and troubleshooting skills.
- Extensive Docker and container runtime experience.
- Strong understanding of networking fundamentals.
- Strong communication skills with the ability to explain design choices and trade-offs to both technical and non-technical stakeholders.
- Collaborative working style, comfortable facilitating cross team discussions and design workshops.
- Self-driven, structured, and able to balance long term architectural direction with hands on design review and support.
Do you have questions?
We look forward to receiving your complete application documents stating your earliest start date.
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