Principal Forward Deployed Engineer

Broadcom

Principal Forward Deployed Engineer modernizing enterprise infrastructure, Kubernetes, and AI platforms for Broadcom’s complex enterprise customers. Driving migrations, production code contributions, and product roadmap influence.

Posted 9/4/2026full-timeRemote • Colorado • 🇺🇸 United StatesLead💰 $132,200 - $211,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in architecting and deploying high-throughput AI inferencing pipelines and Kubernetes architectures, with a strong focus on cloud-native solutions and integration strategies. Proven ability to lead technical initiatives and mentor teams while engaging effectively with C-suite stakeholders.

Highest-signal resume keywords

Kubernetes ArchitectureAI Inferencing PipelinesCloud-Native Migration StrategiesProduction Systems DesignTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

KubernetesAI PlatformsGoPythonJavaVSphereNVIDIA vGPUCRDsGitOpsDistributed Systems

Soft Skills

Technical CredibilityMentoringStakeholder Engagement

Tools & Technologies

ArgoCDFluxOpenShiftEKSGKEAKSApache KafkaRabbitMQPulsarApache Spark

Industry Keywords

Infrastructure SoftwareEnterprise AccountsProduction-Grade SystemsReal-Time LLM InferencingCloud-Native Pathways

Tech Stack

Tools & technologies

ApacheCassandraCloudDistributed SystemsFluxGoJavaKafkaKubernetesOpenShiftOraclePulsarPythonRabbitMQRayRedisSparkVMware

About the role

Key responsibilities & impact

Serve as an elite technical authority, enterprise strategist, and field-to-engineering leader across the Infrastructure Software Division
Embed with complex enterprise accounts during platform modernizations, bare-metal replatforming, stateful workload migrations, and AI inferencing deployments
Bridge core engineering, product management, executive leadership, and C-level enterprise customer architects
Architect, scale, and validate production-grade vSphere Kubernetes Service and VMware Cloud Foundation topologies
Design and deploy production systems for real-time LLM inferencing, RAG pipelines, and distributed AI runtime frameworks across GPU clusters
Lead end-to-end migration strategies from legacy bare-metal systems, risk calculation platforms, stateful engines, and fragmented AI workloads to cloud-native Kubernetes
Engineer prototype integrations and write production operators/CRDs to unblock strategic accounts, upstreaming contributions into core ISG codebases
Convert customer pain points, field workarounds, and architectural patterns into product requirements and roadmap priorities
Set technical patterns for containerizing, tuning, and orchestrating distributed systems including Kafka, Pulsar, vector databases, in-memory grids, and AI data/compute engines
Define cross-platform integration strategies across competing Kubernetes distributions
Establish deployment standards, GitOps frameworks, and CAPI/Operator patterns across the FDE organization
Mentor Senior and Staff FDEs

Requirements

What you’ll need

10+ years of software engineering experience
5+ years driving high consequence infrastructure, distributed systems, AI platforms, or Kubernetes architectures at scale
17+ years related experience required
Proven ability to command technical credibility with C-suite stakeholders while remaining hands-on in production code
Authority-level mastery of Kubernetes internal mechanics, CRDs, Kubernetes Operators, Cluster API (CAPI), and GitOps architecture including ArgoCD and Flux
Extensive experience architecting high-throughput AI inferencing pipelines and virtualized GPU environments, including NVIDIA vGPU, MIG, and GPUDirect RDMA
Experience with model serving frameworks including vLLM, TGI, and Triton
Proven track record architecting and running high-throughput, low-latency stateful workloads on Kubernetes
Experience with Ray, vLLM, SGLang, LeaderWorkerSets, vLLM-Orchestrator, Milvus, Qdrant, Pinecone, Apache Cassandra, ScyllaDB, Oracle Coherence, Hazelcast, Redis, Apache Ignite, Apache Kafka, RabbitMQ, Pulsar, Apache Spark, Apache Flink, Dask, and Trino/Presto
Deep experience migrating enterprise monoliths, mainframe/bare metal environments, and siloed AI hardware deployments to zero-downtime cloud-native pathways
Hands-on experience developing in Go, Python, or Java for systems-level infrastructure, Kubernetes controllers, custom AI wrappers, or automation frameworks
Technical fluency across OpenShift, EKS, GKE, AKS, Rancher RKE/RKS, and networking/storage technologies including CSI/CNI, RDMA, InfiniBand, and RoCEv2
Bachelor's degree preferred; relevant years of experience in lieu of a degree may be considered

Benefits

Comp & perks

Discretionary annual bonus
Competitive new hire equity grant
Annual equity awards
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
Vacation time
Paid Family Leave and other leaves of absence according to applicable laws