Forward Deployed Engineer (Staff)

What you'll do

• Write production code and build prototype integrations directly within customer production environments.
• Architect, deploy, and maintain production-grade vSphere Kubernetes Service (VKS) clusters on hybrid cloud infrastructure.
• Lead technical migrations of bare metal environments and legacy data stacks to cloud-native Kubernetes targets.
• Deploy and scale production AI inferencing workloads, RAG architectures, and vector search frameworks using virtualized GPUs.
• Containerize and migrate heavy stateful engines, message brokers, and distributed caches onto Kubernetes.
• Troubleshoot live networking, storage, and GPU failures while optimizing VKS performance for enterprise clients.
• Translate field-tested code and customer pain points into prioritized product requirements for core engineering teams.
• Manage the full engagement lifecycle from initial architecture and discovery through go-live and operational stabilization.

What we're looking for

• 12+ years of related experience required.
• Bachelor's degree preferred.
• Experience functioning within or alongside core software/R&D divisions rather than pure IT or professional services.
• Hands-on experience operating GPU accelerated Kubernetes nodes, model serving runtimes, and distributed AI orchestration.
• Hands-on experience containerizing and operating high throughput/low latency platforms including distributed caching, messaging, and analytics engines.
• Deep technical knowledge of deploying and scaling containerized data services, AI engines, and orchestrators like Ray, Spark, and Flink.
• Advanced skills in Terraform, Helm, Kubernetes Operators, Cluster API, and GitOps tools like ArgoCD or Flux.
• Technical depth across competing enterprise Kubernetes distributions such as OpenShift, EKS, GKE, AKS, or Rancher.