Forward Deployed Engineer (Principal)

What you'll do

• Architect and validate production-grade vSphere Kubernetes Service and VMware Cloud Foundation topologies for mission-critical deployments.
• Design and deploy production systems for real-time LLM inferencing and distributed AI runtime frameworks on GPU clusters.
• Lead end-to-end technical migration strategies for legacy bare metal systems to unified cloud-native Kubernetes targets.
• Engineer high-value prototype integrations and write production operators or CRDs to unblock strategic enterprise accounts.
• Upstream field innovations and code contributions directly into the core infrastructure software codebases.
• Synthesize customer pain points into concrete product requirements to influence the multi-year technical roadmap.
• Establish deployment standards, GitOps frameworks, and CAPI/Operator patterns across the broader engineering organization.
• Define cross-platform integration strategies for clients operating mixed environments across competing Kubernetes distributions.

What we're looking for

• 17+ years of related experience is required.
• 10+ years of software engineering experience is required.
• 5+ years of experience driving high consequence infrastructure, distributed systems, AI platforms, or Kubernetes architectures at scale is required.
• Bachelor's degree is preferred.
• Authority level mastery of Kubernetes internals, CRDs, Operators, Cluster API, and GitOps architecture is required.
• Extensive experience architecting AI inferencing pipelines, virtualized GPU environments, and distributed inference topologies is required.
• Hands-on experience developing in Go, Python, or Java for systems level infrastructure or Kubernetes controllers is required.
• Proven track record architecting high throughput stateful workloads including vector databases, messaging systems, and data engines is required.