Forward Deployed Engineer – Staff

This is a fully remote position, open to applicants in Colorado, +4 more states.

📋 Description

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

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

• Identify recurring migration hurdles and usability issues within customer environments.

• Develop and test field solutions to accelerate feature iteration cycles.

• Manage engagements from pre-migration discovery to go-live and operational stabilization.

• Partner with client engineers in production settings.

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

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

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

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

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

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

• Architect operator-driven, cloud-native deployments for data processing, orchestration, and distributed AI frameworks.

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

⛳️ Requirements

• Minimum of 12 years of relevant experience required.

• Strong alignment with product engineering workflows.

• Experience working within or closely alongside core software/R&D divisions rather than solely in IT or professional services.

• Demonstrated history of maintaining strong engagement with customer technical leadership and developers throughout long-term, complex engineering projects.

• Ability to convert raw technical customer requirements and field workarounds into precise product specifications and feature requests.

• Practical experience operating GPU-accelerated Kubernetes nodes.

• Familiarity with model serving runtimes, including vLLM, TGI, and Triton Inference Server.

• Experience with vector databases such as Milvus, Qdrant, and Pgvector.

• Knowledge of distributed AI orchestration tools, including Ray and KubeRay.

• Hands-on experience in containerizing and managing high throughput/low latency platforms.

• Proficiency with Redis, Oracle Coherence, Hazelcast, Hadoop (HDFS/YARN), Apache Kafka, RabbitMQ, and Pulsar.

• In-depth technical expertise in containerized data services, AI engines, and orchestrators.

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

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

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

• Bachelor's degree preferred; relevant years of experience may be considered in lieu of a degree.

🏝️ Benefits

• Discretionary annual bonus.

• Competitive new hire equity grant.

• Annual equity awards.

• Medical plans.

• Dental plans.

• Vision plans.

• 401(K) participation with company matching.

• Employee Stock Purchase Program (ESPP).

• Employee Assistance Program (EAP).

• Company-paid holidays.

• Paid sick leave.

• Vacation time.

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