Forward Deployed Engineer – Staff

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

📋 Description

• Serve as an embedded engineering liaison within the Infrastructure Software Division, collaborating with core software architects, product managers, and enterprise client developers to reduce deployment friction.

• Detect recurring migration obstacles and platform usability issues in customer settings, quickly developing and testing field solutions.

• Manage the engagement lifecycle from pre-migration discovery to go-live and operational stabilization.

• Collaborate with client engineers in production settings to write code, create manifests, debug networking, storage, and GPU issues, and enhance VKS performance.

• Integrate field-tested code, architectural patterns, and customer challenges into essential engineering requirements and prioritized platform features.

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

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

• Deploy, tune, and scale production AI inferencing workloads, RAG architectures, vector search, and model-serving frameworks on Kubernetes utilizing virtualized GPU resources.

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

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

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

⛳️ Requirements

• Strong alignment with product engineering workflows; experience working within or closely with core software/R&D divisions rather than solely in IT or professional services.

• Demonstrated history of staying actively engaged with customer technical leadership and developers throughout long-term, complex engineering projects.

• Proven ability to convert raw technical customer needs and field workarounds into clear product specifications and feature requests for core development teams.

• Hands-on experience managing GPU accelerated Kubernetes nodes, model serving runtimes (vLLM, TGI, Triton Inference Server), vector databases (Milvus, Qdrant, Pgvector), and distributed AI orchestration (Ray, KubeRay).

• Practical experience in containerizing and operating high throughput/low latency platforms, including Redis, Oracle Coherence, Hazelcast, risk calculation platforms, Hadoop (HDFS/YARN), Apache Kafka, RabbitMQ, and Pulsar.

• Extensive technical knowledge of deploying, tuning, and scaling containerized data services, AI engines, and orchestrators including 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 (ArgoCD, Flux).

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

• Minimum of 12 years of related experience required.

🏝️ 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.