Forward Deployed Engineer – Staff

This is a fully remote position, open to applicants in California, +5 more states.

📋 Description

• Serve as an embedded engineering liaison within the Infrastructure Software Division.

• Collaborate with core software architects, product managers, and enterprise client developers to reduce deployment challenges.

• Recognize migration obstacles and platform usability issues, and swiftly develop and test field solutions.

• Manage customer interactions from pre-migration assessment to go-live and operational stabilization.

• Write production-grade code, create manifests, troubleshoot live networking, storage, and GPU failures, and enhance VKS performance.

• Convert field-tested code, architectural patterns, and customer challenges into prioritized platform features.

• Design, implement, and maintain production-quality VKS clusters across VMware Cloud Foundation and hybrid cloud infrastructures.

• Spearhead migrations from enterprise, bare-metal, and legacy platforms to VKS or cloud-native Kubernetes.

• Deploy, optimize, and scale AI inferencing, RAG, vector search, and model-serving workloads on Kubernetes.

• Containerize, refactor, and transition stateful engines, message brokers, distributed caches, and analytics platforms.

• Design cloud-native deployments for contemporary data processing, orchestration, and distributed AI frameworks.

• Advise clients who are evaluating or utilizing VKS alongside other Kubernetes distributions.

⛳️ Requirements

• Bachelor's degree preferred; relevant experience may be accepted in place of a degree.

• A minimum of 12 years of related experience is required.

• Strong alignment with product engineering workflows and experience within or adjacent to core software/R&D divisions.

• Demonstrated ability to engage with customer technical leadership and developers throughout long-term, complex engineering initiatives.

• Capacity to translate customer needs and field workarounds into product specifications and feature requests.

• Practical experience managing GPU-accelerated Kubernetes nodes.

• Familiarity with vLLM, TGI, Triton Inference Server, Milvus, Qdrant, Pgvector, Ray, and KubeRay.

• Experience in containerizing and operating distributed caching, in-memory grids, compute and analytics engines, messaging, and streaming platforms.

• Extensive technical knowledge of containerized data services, AI engines, and orchestrators.

• Technical proficiency across OpenShift, EKS, GKE, AKS, or Rancher RKE/RKS.

• Advanced skills in Terraform, Helm, Kubernetes Operators (KPO), Cluster API (CAPI), and GitOps using ArgoCD or Flux.

🏝️ Benefits

• Discretionary annual bonus.

• Competitive equity grant for new hires.

• Annual equity awards.

• Medical, dental, and vision plans.

• Participation in a 401(K) plan with company matching.

• Employee Stock Purchase Program (ESPP).

• Employee Assistance Program (EAP).

• Company-paid holidays.

• Paid sick leave and vacation time.

• Paid Family Leave and other leaves of absence in accordance with applicable laws.