Forward Deployed Engineer – Kubernetes

This is a fully remote position, open to applicants in Tennessee.

📋 Description

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

• Collaborate with software architects, product managers, and enterprise client developers to streamline deployment processes.

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

• Stay integrated with customer technical teams from the initial migration discovery through to go-live and operational stabilization.

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

• Convert field-tested code, architectural frameworks, and customer challenges into prioritized platform functionalities.

• Design, deploy, and manage production-grade VKS clusters across VMware Cloud Foundation and hybrid cloud setups.

• Direct migration strategies for enterprise platforms, bare metal settings, and legacy data environments to VKS or cloud-native Kubernetes.

• Implement, adjust, and expand AI inferencing workloads, RAG architectures, vector search, and model-serving frameworks on Kubernetes.

• Containerize, refactor, and transition stateful engines, message brokers, distributed caches, and risk calculation/analytics platforms to Kubernetes.

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

• Advise clients assessing or using VKS alongside OpenShift, EKS, GKE, AKS, and Rancher distributions.

⛳️ Requirements

• Minimum of 12 years of relevant experience required.

• Bachelor's degree is preferred.

• Consideration may be given to relevant experience in lieu of a degree.

• Strong alignment with product engineering processes and experience within or alongside core software/R&D divisions.

• Demonstrated experience with long-term, intricate engineering projects involving customer technical leadership and developers.

• Ability to convert technical 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 managing distributed caching, in-memory grids, compute and analytics engines, messaging, and streaming platforms.

• Technical expertise in Ray, vLLM, Apache Spark, Apache Flink, Dask, Apache Airflow, Prefect, Dagster, Argo Workflows, Trino/Presto, Apache Cassandra/ScyllaDB, Elasticsearch/OpenSearch, Milvus, and Qdrant.

• In-depth technical knowledge of OpenShift, EKS, GKE, AKS, or Rancher RKE/RKS.

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

🏝️ Benefits

• Discretionary annual bonus.

• Competitive new hire equity grant.

• Annual equity awards.

• Medical, dental, and vision plans.

• 401(K) participation 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.