Principal AI Network Hardware Systems Engineer

Microsoft

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Salary
$142,800–$274,800 / yr
Posted
15 days ago
Freshness
Confirmed live yesterday
Closes
Feb 23, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $199k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 62% of similar roles. Most pay $161,600–$235,750 — the shaded band above. At the midpoint, this role pays about $209k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 598 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 586 roles with salary data.

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At a glance

TL;DR · Principal AI Network Hardware Systems Engineer

The Principal AI Network Hardware Systems Engineer joins the Platform Systems Engineering team to lead the architecture, bring-up, validation, and deployment of networking infrastructure for the MAIA AI platform. This role involves developing requirements for large-scale training and inference clusters while collaborating across silicon, firmware, and software teams to deliver scalable solutions. The engineer will manage the full networking stack, including high-speed SerDes, optics, NICs, switch silicon, and RDMA-based technologies like RoCE, ECN, PFC, and DCQCN. Key responsibilities include designing IP-based solutions involving TCP/IP, UDP, and congestion management, as well as performing packet-level analysis and automated performance characterization. The role addresses the technical challenge of optimizing high-performance AI fabrics and distributed training systems to ensure reliability across large-scale infrastructure. Required expertise includes GPU-based system development and high-speed interface architecture for 200G/400G/800G Ethernet environments.

What you'll do

  • Define networking requirements and architectural roadmaps for large-scale AI training and inference clusters.
  • Design and validate IP-based networking solutions including TCP/IP, routing, congestion management, and traffic engineering.
  • Optimize RDMA-based networking solutions and collective communication efficiency for AI fabrics.
  • Develop validation strategies to characterize network performance, latency, and bandwidth under heavy AI workloads.
  • Lead end-to-end troubleshooting of hardware and protocol issues using packet analysis and telemetry tools.
  • Build automated tools for network validation, performance analysis, and failure detection.
  • Create observability frameworks to monitor network health and improve engineering productivity.

What we're looking for

  • Master's degree in Engineering or related field and 7+ years of technical engineering experience.
  • Bachelor's degree in Engineering or related field and 8+ years of technical engineering experience.
  • 8+ years of experience in network hardware development.
  • 8+ years of experience in GPU based system/software development.
  • 8+ years of hands-on experience with high-speed interface architecture and development.
  • Ability to pass the Microsoft Cloud Background Check.
  • Experience with RDMA, RoCE, congestion control, and AI fabric technologies is preferred.
  • Experience with network switches, SmartNICs, DPUs, and large-scale cloud infrastructure is preferred.

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