Forward Deployed Engineer (Principal)

Broadcom•USA - Colorado - Remote location, CO

2d•$132,200 - $211,500

About The Position

We are seeking a Forward Deployed Engineer (Principal) to serve as an elite technical authority, enterprise strategist, and field to engineering leader across the Infrastructure Software Division (ISG). In this high impact role, you will embed with our largest, most complex enterprise accounts during critical platform modernizations, bare metal re platforming, large scale stateful workload migrations, and mission critical AI inferencing deployments. As a Principal member of the core Engineering organization, you will operate at the intersection of enterprise architecture, hands on production code, and long term product strategy. You will tackle systemic architecture blockers in high stakes environments, author reference implementations, and directly influence the multi year technical roadmap of our core infrastructure and AI platform software. Unlike traditional pre sales, professional services, or post sales support roles, the Principal FDE functions as a senior extension of R&D in the field. Your mission is to eliminate enterprise adoption friction at scale, codify repeatable deployment patterns for modern workloads (including distributed AI models), and establish a high bandwidth feedback loop that turns field innovations directly into core software capabilities.

Requirements

10+ years of software engineering experience with 5+ years driving high consequence infrastructure, distributed systems, AI platforms, or Kubernetes architectures at scale. Demonstrated alignment with core R&D/Product Engineering organizations.
Proven ability to command technical credibility with C suite stakeholders (CTOs, VP of Infra, Chief AI Officers) while remaining deeply hands on in production code with staff level customer engineers.
Authority level mastery of Kubernetes internal mechanics, Custom Resource Definitions (CRDs), Kubernetes Operators, Cluster API (CAPI), and GitOps architecture (ArgoCD, Flux).
Extensive experience architecting high throughput AI inferencing pipelines, virtualized GPU environments (NVIDIA vGPU, MIG, GPUDirect RDMA), model serving frameworks (vLLM, TGI, Triton), and distributed inference topologies.
Proven track record architecting and running high throughput, low latency stateful workloads on Kubernetes: AI Serving & Distributed Compute: Ray, vLLM, SGLang, LeaderWorkerSets (LWS), vLLM-Orchestrator. Vector & NoSQL Databases: Milvus, Qdrant, Pinecone, Apache Cassandra, ScyllaDB. In Memory & Caching: Oracle Coherence, Hazelcast, Redis, Apache Ignite. Messaging & Streaming: Apache Kafka, RabbitMQ, Pulsar. Data & Analytics Engines: Apache Spark, Apache Flink, Dask, Trino/Presto.
Deep experience untangling complex enterprise monoliths, mainframe/bare metal environments, and siloed AI hardware deployments to construct seamless zero downtime migration pathways.
Hands on experience developing in Go, Python, or Java for systems level infrastructure, Kubernetes controllers, custom AI wrappers, or automation frameworks.
Comprehensive technical fluency across competing enterprise distributions (OpenShift, EKS, GKE, AKS, Rancher RKE/RKS) and their underlying networking (CSI/CNI, RDMA, InfiniBand, RoCEv2) and storage abstractions.
17+ years related experience required

Nice To Haves

Bachelor's degree preferred. Relevant year's experience in lieu of a degree may be considered.

Responsibilities

Act as the primary technical authority bridging core engineering, product management executive leadership, and C level enterprise customer architects.
Architect, scale, and validate production grade vSphere Kubernetes Service (VKS) and VMware Cloud Foundation (VCF) topologies for high consequence, mission critical, and highly regulated deployments.
Design and deploy production systems for real time LLM inferencing, Retrieval Augmented Generation (RAG) pipelines, and distributed AI runtime frameworks across high density GPU clusters.
Lead end to end technical migration strategies transitioning massive legacy bare metal systems, risk calculation platforms, heavy stateful engines, and fragmented AI workloads to unified cloud native Kubernetes targets.
Directly engineer high value prototype integrations, write production operators/CRDs in the field to unblock strategic accounts, and upstream those contributions directly into core ISG codebases.
Systematically synthesize complex customer pain points, field workarounds, and architectural patterns into concrete product requirements. Partner with VP/Director level Product Managers to prioritize features that shorten software iteration cycles from months to days across the global product suite.
Set technical patterns for containerizing, tuning, and orchestrating heavy distributed systems, including streaming platforms (Kafka, Pulsar), vector databases (Milvus, Qdrant), in memory grids (Coherence, Redis), and advanced AI data/compute engines (Ray, vLLM, Spark, Flink).
Define cross platform integration strategies for clients operating mixed environments across competing distributions (Red Hat OpenShift, EKS, GKE, AKS, Rancher).
Establish best in class deployment standards, GitOps frameworks, and CAPI/Operator patterns across the broader FDE organization; mentor Senior and Staff FDEs to elevate team wide execution capabilities.