Microsoft

Senior AI Network Systems Engineer

Microsoft$119K — $234K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Master's or Bachelor's Degree in Engineering with relevant technical experience (3-5 years)
  • 5+ years of networking experience specifically for accelerator-based systems
  • 5+ years of hands-on design and troubleshooting of Ethernet networking infrastructures
  • Extensive background in AI, HPC, or large-scale data center deployments
  • Ability to meet stringent Microsoft security screening requirements.

Responsibilities

  • Define networking requirements for AI training clusters
  • Collaborate across teams to develop scalable networking solutions
  • Influence AI networking architecture through reviews and roadmaps
  • Establish network operation concepts for AI infrastructure
  • Lead design of IP-based networking solutions for performance optimization
  • Analyze performance in distributed AI workloads and optimize communication paths
  • Conduct thorough debugging and root cause analysis across networking layers

Benefits

  • Eligible for Microsoft Cloud Background Check every two years
  • Opportunity for hands-on work with cutting-edge AI technologies
  • Collaborate with industry-leading engineers and researchers
  • Work in a dynamic, high-performance engineering environment
  • Contribution to next-generation AI networking innovations
Full Job Description
Responsibilities

AI Network Architecture & System Integration

  • Define and develop networking requirements for large-scale AI training and inference clusters.


  • Collaborate with silicon, system software, firmware, hardware, and Azure infrastructure teams to deliver scalable networking solutions from concept through datacenter deployment.


  • Participate in architecture reviews and influence next-generation AI networking roadmaps.


  • Define network concepts of operation, serviceability requirements, telemetry requirements, and operational models for AI infrastructure.


Layer 3 / Layer 4 Networking

  • Lead design and validation of IP-based AI networking solutions spanning TCP/IP, UDP, routing, congestion management, flow control, QoS, and traffic engineering.


  • Analyze transport-layer behavior and performance characteristics across large-scale distributed AI workloads.


  • Evaluate network protocol implementations and debug issues impacting latency, throughput, scalability, and reliability.


  • Drive optimization of network communication paths supporting distributed AI training and inference.


RDMA & AI Fabric Technologies

  • Design, validate, and optimize RDMA-based networking solutions for AI clusters.


  • Analyze RDMA performance, congestion behavior, packet loss, retransmissions, and collective communication efficiency.


  • Work closely with networking vendors and software teams to optimize AI fabric performance and workload scalability.


  • Develop validation methodologies for AI traffic patterns and collective communication workloads.


Performance Characterization & Validation

  • Develop and execute networking validation strategies covering functionality, performance, scale, interoperability, resiliency, and reliability.


  • Characterize network behavior under AI training and inference workloads.


  • Evaluate latency, bandwidth utilization, congestion events, flow distribution, and workload communication patterns.


  • Create and automate network stress, scale, and performance qualification methodologies.


Debugging & Root Cause Analysis

  • Lead end-to-end troubleshooting of networking issues across physical, data link, network, and transport layers.


  • Perform packet-level analysis and protocol debugging using telemetry, packet captures, performance counters, and diagnostic tools.


  • Investigate network switch, NIC, RDMA, routing, congestion control, and protocol-related issues.


  • Drive corrective actions and long-term reliability improvements using fleet telemetry and lab validation.


Automation & Observability

  • Build and improve network observability, diagnostics, telemetry, and monitoring solutions.


  • Develop tools and automation for network validation, performance analysis, and failure detection.


  • Improve engineering productivity through automated testing, qualification, and network health assessment frameworks.


Qualifications

Required Qualifications:
  • Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years technical engineering experience
    • OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years technical engineering experience
    • OR equivalent experience.
  • 5+ years of experience developing or validating networking for accelerator based systems.
  • 5+ years of experience designing, integrating, validating, or troubleshooting Ethernet-based networking infrastructure, including Network switches.
  • 5+ years of experience supporting AI, HPC, cloud, or large-scale data center infrastructure deployments.


Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.


Preferred Qualifications

  • Experience with RDMA technologies, AI fabrics, and distributed training environments.


  • Understanding of RoCE, congestion control, ECN, PFC, DCQCN, and related AI networking technologies.


  • Experience with AI/ML workload communication patterns and collective operations.


  • Experience with SONiC, Linux networking, networking telemetry, and network operating systems.


  • Experience with network switches, SmartNICs, DPUs, NIC offloads, and large-scale cloud infrastructure.


  • Familiarity with AI networking technologies including Ultra Ethernet and hyperscale AI cluster architectures.


  • Experience developing network stress tools, validation frameworks, performance benchmarks, or observability solutions.


  • Knowledge of packet analysis tools, telemetry infrastructure, and network automation frameworks.


  • Exposure to high-speed networking environments (200G/400G/800G Ethernet).


#azure #MAIA #AI/ML #Networking

Hardware Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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Microsoft is an American multinational corporation that develops, manufactures, licenses, supports, and sells a range of software products and services. Microsoft’s devices and consumer (D&C) licensing segment licenses the Windows operating system and related software, Microsoft Office for consumers, and the Windows Phone operating system. The company’s computing and gaming hardware segment provides Xbox gaming and entertainment consoles and accessories, second-party and third-party video games, and Xbox Live subscriptions; surface devices and accessories; and Microsoft PC accessories. Its phone hardware segment offers Lumia smartphones and other non-Lumia phones. Its D&C segment provides Windows Store, Xbox Live transactions, and Windows phone store; search advertising; display advertising; Office 365 Home and Office 365 Personal; first-party video games; and other consumer products and services as well as operating retail stores. Microsoft’s commercial licensing segments license server products, including Windows Server, Microsoft SQL Server, Visual Studio, System Center, and related Client Access Licenses (CALs); Windows Embedded; Windows operating system; Microsoft Office for business, including Office, Exchange, SharePoint, Lync, and related CALs; Microsoft Dynamics business solutions; and Skype. Its commercial segment offers enterprise services, including premier support services and Microsoft consulting services; commercial cloud comprising Office 365 Commercial, other Microsoft Office online offerings, Dynamics CRM Online, and Microsoft Azure; and other commercial products and online services. The company markets and distributes its products through original equipment manufacturers, distributors, and resellers, as well as online.

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Learn more about Microsoft
Size
181,000 employees
Market Cap
$1,762.4 billion
Industry
Net Income
$51.3 billion
Founded
1975
5 Year Trend
+15.5%
Revenue
$153.2 billion
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