Senior Platform Engineer – Kubernetes & Middleware Platforms

Overview

The Role

We’re seeking a strategic technologist and Kubernetes/Container platform engineer with overall 15+ years’ experience to lead and scale our Kubernetes container platform and middleware stack. You will architect, deploy, operate, and evolve high‑availability Kubernetes infrastructure (EKS and Open Shift), ensuring seamless middleware operations (Kafka, Redis Enterprise Cluster, 3

Scale API Gateway). You will automate container deployment (ArgoCD), enforce container security and network policies, oversee capacity planning, helm chart development, and define policies-as-code governance across the environment.

Your mission is to deliver a hardened, future-ready platform that enables multiple engineering teams to develop, deploy, and scale cloud-native applications reliably and securely.

• Design and implement infrastructure abstractions and APIs that simplify deploying AI workloads using Kubernetes-native operations and Git Ops patterns.
• Architect, deploy, and manage Kubernetes platforms (AWS EKS and Red‑Hat Open Shift) across different environments.
• Implement Git Ops workflows with ArgoCD to manage declarative app deployments.
• Design and operate middleware infrastructure:
• Highly available Kafka clusters (mirroring, partitioning, tooling)
• Managed Redis Enterprise clusters (sharding, high‑availability, replication)
• 3
  
  Scale API Gateway development and administration
• Build and manage helm charts, templating, parameterization, and versioning for both platform and middleware stacks.
• Enforce container security and policy governance using policies-as-code tools (e.g. OPA, Kyverno), scanning (e.g. Clair, Snyk), and automated admission controls.
• Implement network policies (Kubernetes Network Policy / Calico) to enforce segmentation and micro‑segmentation.
• Configure and manage service mesh (e.g. Istio, Linkerd) for observability, traffic controls, and secure service‑to‑service communication.
• Conduct capacity planning, cluster sizing, resource tuning, and autoscaling strategies.
• Conduct architecture reviews, train engineers, and drive platform best practices across teams.
• Partner with SREs to define platform SLAs, uptime targets, resilience benchmarks, and alerting/monitoring.
• Lead incident response and root cause analysis, automating recovery workflows and improving platform resiliency.

• 15+ years of overall engineering experience, including:
• At least 8+ years with Kubernetes platforms (EKS, Open Shift) in production.
• Experienced in managing streaming and caching infrastructure at scale (Kafka, Redis Enterprise Clusters).
• Prior hands-on administration or development of API Management / Gateway platforms - preferably Red Hat 3
  
  Scale
• Demonstrated ability to collaborate with cross-functional teams to deploy AI workloads on Kubernetes or cloud-native platforms.
• Deep knowledge of Dev Sec Ops  principles, container security, governance, and compliance in enterprise environments.
• Strong automation experience:
  Helm, Git Ops, ArgoCD, IaC (Terraform/AWS-Cloud Formation/Ansible).
• Experience configuring service mesh, network policy controls, and multi-tenancy in Kubernetes.
• Demonstrated expertise in scripting languages such as Python, Bash, Groovy, or equivalent; hands‑on experience developing automation tooling, custom Kubernetes operators/controllers, or other platform‑level integrations. A candidate with a software development background or experience building production-grade automation frameworks is strongly preferred.
• Thorough understanding of core Kubernetes concepts, and observability tooling.
• Demonstrated experience in capacity planning, cluster sizing, and performance tuning for critical infrastructure.
• Strong troubleshooting skills across Kubernetes, middleware, and distributed systems; experienced in leading incident response and root cause analysis.

• EKS and/or Open Shift administration certification (CKA, AWS Certified Kubernetes Administrator, Red Hat Certified Open Shift Administrator, or equivalent).
• Knowledge of middleware architecture for high-throughput, low-latency messaging systems.
• Experience with cloud cost optimization, chargeback models.
• Familiarity with…