Forward Deployed Engineer (Principal)

Broadcom; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

Broadcom seeks a Forward Deployed Engineer (Principal) to act as the technical authority and field leader across ISG. You will embed with large enterprise accounts during platform modernizations, AI deployments, and complex migrations.

You will drive architecture, write reference implementations, and shape the multi-year roadmap, bridging R&D with customer needs while mentoring engineers across the product suite.

Qualifications

• 10+ years of software engineering experience.
• 5+ years infra, distributed systems, AI platforms, or Kubernetes at scale.
• Proven ability to command technical credibility with C-suite stakeholders while remaining hands-on.
• Mastery of Kubernetes primitives: CRDs, Operators, CAPI and GitOps architecture.

Responsibilities

• Bridge core engineering, product management, and executive leadership.
• Architect, scale, and validate production-grade Kubernetes service topologies for high-consequence deployments.
• Design production AI inference pipelines and distributed runtimes across GPU clusters.
• Lead end-to-end migration strategies from legacy systems to cloud-native Kubernetes.
• Engineer high-value prototype integrations and upstream contributions into ISG codebases.
• Influence product strategy and roadmaps based on field feedback and customer pain points.

Skills

Senior Engineer

Customer Authority

Kubernetes Mastery

AI Infra Fluency

Distributed Systems

Tools

CRDs

Kubernetes Operators

GitOps (ArgoCD/Flux)

Job description

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Job Description:

Position Description

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.

Key Responsibilities

• Divisional Field to Engineering Leadership: Act as the primary technical authority bridging core engineering, product management executive leadership, and C level enterprise customer architects.
• Strategic Architecture & Reference Design: 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.
• Enterprise AI & Distributed Inferencing Acceleration: 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.
• Large Scale Migration Strategy: 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.
• Mission Critical Problem Solving & Code Contribution: 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.
• Product Strategy & Roadmap Influence: 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.
• Complex Stateful & AI Data Fabric: 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).
• Multi Cloud & Competitive Interoperability: Define cross platform integration strategies for clients operating mixed environments across competing distributions (Red Hat OpenShift, EKS, GKE, AKS, Rancher).
• Technical Mentorship & Practice Building: 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.

Key Qualifications

• Principal Level Engineering Stature: 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.
• Strategic Customer Authority: 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.
• Deep Kubernetes & Cloud Native Primitives: Authority level mastery of Kubernetes internal mechanics, Custom Resource Definitions (CRDs), Kubernetes Operators, Cluster API (CAPI), and GitOps architecture (ArgoCD, Flux).
• AI & GPU Infrastructure Fluency: 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.
• Distributed Statefull Systems Expertise: Proven track record architecting and running high throughput, low latency stat