Forward Deployed Engineer (Staff)

We are seeking a hands-on, highly engaged Forward Deployed Engineer (Staff) who specializes in Kubernetes, platform modernization, large-scale stateful workload migration, and enterprise AI infrastructure. This role sits directly within the Engineering Business Unit, working side by side with product and core software teams. Unlike traditional professional services or post-sales support, our Forward Deployed Engineering team operates as an extension of core engineering in the field. ## Core Mission Reduce customer adoption friction, dramatically shorten software iteration cycles, and establish a high-bandwidth, direct feedback loop between real-world enterprise deployments and product development. ## What You'll Do You will be embedded directly alongside enterprise client teams throughout the entire end-to-end lifecycle of an engagement—from initial architecture, bare metal/legacy re-platforming, and AI cluster setup to live field troubleshooting and production rollout. Because you are part of the core Engineering organization, you won't just file bug reports; you will write production code in the field, build prototype integrations, and channel those contributions directly back to engineering teams across the Infrastructure Software Division (ISG) to shape, prioritize, and accelerate high-impact platform capabilities. Key responsibilities include acting as an embedded engineering liaison across the Infrastructure Software Division, identifying recurring migration blockers and platform usability gaps, rapidly building and testing field fixes to shorten feature iteration cycles from months to days. You will stay actively embedded with customer technical teams from pre-migration discovery through go-live and operational stabilization, work shoulder-to-shoulder with client engineers to write code, build manifests, debug live networking/storage/GPU failures, and optimize VKS performance. You will synthesize field-tested code, architectural patterns, and customer pain points into core engineering requirements, partnering with product managers and core engineers to translate customer contributions into prioritized platform features. You will architect, deploy, and maintain production-grade v. Sphere Kubernetes Service (VKS) clusters across VMware Cloud Foundation (VCF) and hybrid cloud infrastructure, optimized for both general-purpose compute and accelerated GPU/NPU workloads. Lead technical migration strategies transitioning enterprise platforms, massive bare metal environments, and legacy data stacks over to VKS or cloud-native Kubernetes targets. Deploy, tune, and scale production AI inferencing workloads, RAG (Retrieval Augmented Generation) architectures, vector search, and model serving frameworks on Kubernetes using virtualized GPU resources (NVIDIA v. GPU, MIG). Containerize, refactor, and migrate heavy stateful engines, message brokers (Apache Kafka, Rabbit. MQ), distributed caches (Redis, Oracle Coherence, Hazelcast), and risk calculation/analytics platforms onto Kubernetes. Architect operator-driven, cloud-native deployments for data processing, orchestration, and distributed AI frameworks (Ray, v. LLM, Apache Spark, Apache Airflow, Trino/Presto, Flink, Dask, Cassandra/Scylla. DB, Milvus/Qdrant). Guide clients evaluating or operating VKS alongside competing distributions (Red Hat Open. Shift, Amazon EKS, Google GKE, Azure AKS, Rancher RKE/RKS). ## What We're Looking For You should have deep alignment with product engineering workflows and experience functioning within or closely alongside core software/R&D divisions rather than pure IT or professional services. A proven track record of staying deeply engaged with customer technical leadership and developers across long-term, complex engineering projects is essential. Demonstrated ability to translate raw technical customer requirements and field workarounds into clean product specifications and feature requests for core development teams. Hands-on experience operating GPU-accelerated Kubernetes nodes, model serving runtimes (v. LLM, TGI, Triton Inference Server), vector databases (Milvus, Qdrant, Pgvector), and distributed AI orchestration (Ray, Kube. Ray). You must have hands-on experience containerizing and operating high-throughput/low-latency platforms: distributed caching and in-memory grids (Redis, Oracle Coherence, Hazelcast), compute and analytics engines (risk calculation platforms, Hadoop HDFS/YARN), messaging and streaming (Apache Kafka, Rabbit. MQ, Pulsar). Deep technical knowledge of deploying, tuning, and scaling containerized data services, AI engines, and orchestrators: batch, real-time & AI processing (Ray, v. LLM, Apache Spark, Apache Flink, Dask), orchestration & workflow (Apache Airflow, Prefect, Dagster, Argo Workflows), query, No. SQL & vector engines (Trino/Presto, Apache Cassandra/Scylla. DB, Elasticsearch/Open. Search, Milvus, Qdrant). Technical depth across competing enterprise Kubernetes distributions (Open. Shift, EKS, GKE, AKS, or Rancher RKE/RKS). Advanced skills in Terraform, Helm, Kubernetes Operators (KPO), Cluster API (CAPI), and Git. Ops (Argo. CD, Flux). ## Experience & Education Bachelor's degree preferred; relevant years of experience in lieu of a degree may be considered. 12+ years related experience required. ## Compensation & Benefits The annual base salary range for this position is USD 110,800.00 to USD 177,300.00. As a valued member of our team, you'll be eligible for a discretionary annual bonus and the opportunity to receive not only a competitive new hire equity grant but also annual equity awards, connecting your success directly to the company's growth (all subject to relevant plan documents and award agreements). Broadcom offers a competitive and comprehensive benefits package: medical, dental, and vision plans, 401(K) participation including company matching, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company-paid holidays, paid sick leave, and vacation time. The company follows all applicable laws for Paid Family Leave and other leaves of absence. Broadcom is proud to be an equal opportunity employer. We will consider qualified applicants without regard to race, color, creed, religion, sex, sexual orientation, national origin, citizenship, disability status, medical condition, pregnancy, protected veteran status, or any other characteristic protected by federal, state, or local law. We will also consider qualified applicants with arrest and conviction records consistent with local law. --- _This job was found on [bandana.com](https://www.bandana.com/?utm_source=jd_attribution&utm_medium=repost)_