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, RAG pipelines, and distributed AI runtime frameworks.
• Lead end-to-end technical migration strategies for transitioning 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 customer pain points into core software codebases to influence the multi-year product roadmap.
• Set technical patterns for containerizing and orchestrating heavy distributed systems like Kafka, vector databases, and in-memory grids.
• Define cross-platform integration strategies for clients operating mixed environments across competing distributions like OpenShift, EKS, and GKE.
• Establish deployment standards, GitOps frameworks, and CAPI patterns while mentoring senior and staff engineers.

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 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 ability to command technical credibility with C-suite stakeholders while remaining hands-on in production code is required.