Forward Deployed Engineer (Staff)

What you'll do

• Write production code and build prototype integrations directly in customer environments to resolve technical hurdles.
• Architect, deploy, and maintain production-grade vSphere Kubernetes Service (VKS) clusters for general compute and GPU workloads.
• Lead the migration of large-scale bare metal environments and legacy data stacks to cloud-native Kubernetes targets.
• Deploy and scale AI inferencing workloads, RAG architectures, and vector search frameworks using virtualized GPU resources.
• Containerize and migrate stateful engines, message brokers, and distributed caches onto Kubernetes platforms.
• Translate field-tested code and customer pain points into prioritized feature requirements for the core engineering team.
• Troubleshoot live networking, storage, and GPU failures in production environments to ensure successful platform adoption.
• Manage infrastructure as code using Terraform, Helm, and GitOps tools like ArgoCD or Flux.

What we're looking for

• Must have at least 12 years of related experience.
• A Bachelor's degree is preferred, though relevant experience may be considered in lieu of a degree.
• Experience with Kubernetes, platform modernization, and large scale stateful workload migration.
• Hands-on experience operating GPU accelerated Kubernetes nodes and distributed AI orchestration tools like Ray or vLLM.
• Expertise in containerizing and operating high throughput systems including Redis, Kafka, RabbitMQ, and Spark.
• Proficiency in Infrastructure as Code and GitOps using Terraform, Helm, and ArgoCD or Flux.
• Technical depth across multiple Kubernetes distributions such as OpenShift, EKS, GKE, AKS, or Rancher.
• Ability to translate field requirements into product specifications for core engineering teams.