Forward Deployed Engineer (Staff)

Broadcom

Confirmed live today Trusted
Remote

Quick summary

Work type
Remote
Location
TXCharlotte, NCTNNYCO
Employment
Full-time
Posted
48 days ago
Freshness
Confirmed live today
Closes
Feb 18, 2027

Market check

Salary context

How this pay compares to similar roles

Similar $203k
$148k $264k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $170,837–$235,000.

Based on 240 similar postings.

Employer

About Broadcom

Broadcom is a global semiconductor and infrastructure software company that designs and markets a wide range of networking, storage, and wireless connectivity solutions. Industry: Semiconductors & Infrastructure Software

Broadcom currently has 280 open roles on FindRole.

Listed pay typically runs $121,900–$195,000 across 169 roles with salary data.

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At a glance

TL;DR · Forward Deployed Engineer (Staff)

The Forward Deployed Engineer (Staff) joins the Infrastructure Software Division to serve as an embedded engineering liaison for enterprise clients. This role involves working directly with core software architects and product managers to eliminate deployment friction and accelerate platform capabilities. You will write production code, build prototype integrations, and manage the end-to-end lifecycle of large-scale stateful workload migrations and AI infrastructure setups. Key responsibilities include architecting vSphere Kubernetes Service clusters, migrating legacy data stacks, and scaling AI inferencing workloads. You will utilize technologies including Kubernetes, Terraform, Helm, and GitOps tools like ArgoCD. Expertise in distributed systems such as Kafka, Redis, and Spark, alongside AI frameworks like Ray and vLLM, is required to solve complex modernization problems for GPU-accelerated and hybrid cloud environments.

What does a Forward Deployed Engineer earn?

Median $219575 from 46 postings across 19 companies.

See salary data

What you'll do

  • Write production code and build prototype integrations directly within customer production environments.
  • Architect and maintain production-grade vSphere Kubernetes Service (VKS) clusters on hybrid cloud infrastructure.
  • Lead technical migrations of bare metal environments and legacy data stacks to Kubernetes targets.
  • Deploy and scale production AI inferencing workloads, RAG architectures, and vector search frameworks.
  • Containerize and migrate heavy stateful engines, message brokers, and distributed caches to Kubernetes.
  • Debug live networking, storage, and GPU failures while optimizing VKS performance for clients.
  • Translate field-tested code and customer pain points into prioritized product requirements for core engineering teams.
  • Identify migration blockers and build rapid field fixes to shorten software iteration cycles.

What we're looking for

  • 12+ years of related experience is required.
  • A Bachelor's degree is preferred.
  • Experience functioning within or alongside core software/R&D divisions is required.
  • Proven track record of staying deeply engaged with customer technical leadership on long-term, complex engineering projects is required.
  • Hands-on experience operating GPU accelerated Kubernetes nodes, model serving runtimes, and distributed AI orchestration is required.
  • Hands-on experience containerizing and operating high throughput/low latency platforms including distributed caching, messaging, and analytics engines is required.
  • Technical depth across competing enterprise Kubernetes distributions like OpenShift, EKS, GKE, AKS, or Rancher is required.
  • Advanced skills in Terraform, Helm, Kubernetes Operators, Cluster API, and GitOps are required.

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