ResponsibilitiesAI Networking Architecture & Platform Development
- Define and drive networking architectures for AI training and inference platforms, spanning scale-up and scale-out deployments. Partner across architecture, silicon, firmware, software, and Azure infrastructure teams to deliver networking solutions from concept through datacenter deployment while influencing future networking roadmaps.
Network Hardware Integration & System Bring-Up
- Lead the integration, bring-up, and deployment of network hardware technologies including switches, NICs, PHYs, high-speed SerDes interfaces, optics, cables, and backplane solutions. Collaborate with internal teams, ODMs, and technology partners to ensure successful qualification and production readiness.
AI Fabric Validation, Performance & Reliability
- Define and execute validation strategies for AI networking infrastructure, including functional, performance, scale, interoperability, reliability, and stress testing. Develop automated qualification frameworks and methodologies to ensure robust operation in rack-scale and cluster-scale AI environments.
Performance Optimization & Networking Efficiency
- Analyze and optimize AI fabric performance across distributed training and inference workloads. Evaluate latency, bandwidth utilization, congestion behavior, and collective communication efficiency, translating workload requirements into scalable networking solutions and architecture recommendations.
High-Speed Interconnect & Emerging Technologies
- Drive qualification and deployment of next-generation networking technologies, including high-speed copper and optical interconnects, PAM4-based SerDes, advanced optics, and future networking innovations such as LPO, LRO, CPO, and silicon photonics. Evaluate technology tradeoffs across performance, power, reliability, and scalability.
Debug, Telemetry & Automation
- Lead root-cause analysis of networking and AI fabric issues spanning physical layer, network protocols, and distributed AI communication layers. Develop telemetry, diagnostics, automation, and fleet monitoring solutions that improve network reliability, accelerate issue resolution, and enhance engineering productivity.
Key Responsibilities
- Drive end-to-end architecture, integration, validation, and deployment of networking infrastructure for AI systems across scale-up and scale-out environments.
- Partner with silicon, firmware, software, hardware, and Azure infrastructure teams to define networking requirements and deliver scalable, reliable, and high-performance AI fabrics.
- Lead bring-up, qualification, and optimization of network subsystems including switches, NICs, PHYs, optics, cables, and high-speed SerDes technologies.
- Develop validation and performance methodologies for AI networking infrastructure, ensuring readiness across functionality, scale, reliability, and stress conditions.
- Drive root-cause analysis, telemetry, and automation solutions to improve network resiliency, operational efficiency, and fleet health.
- Evaluate and influence next-generation networking technologies and architectures required to support future AI workloads and hyperscale deployments.
QualificationsRequired Qualifications:- Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 7+ years technical engineering experience
- OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience
- OR equivalent experience.
- 8+ years of experience with fiber optics, including related tools, devices, processes, design, deployment, operations, or manufacturing.
- 8+ years of experience designing, testing, validating, or troubleshooting optical interconnects, optical components, or end-to-end fiber links.
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:Networking and AI Infrastructure
- Experience with data center networking and AI infrastructure, including GPU fabrics, InfiniBand, Ethernet, or UALink ecosystems.
- Understanding of scale-up and scale-out network architectures and the optical connectivity requirements of large-scale distributed AI systems.
Optical Systems and Interconnect Expertise
- Experience in one or more areas such as high-speed copper or optical interconnects, high-speed optical transmission systems, Co-Packaged Optics (CPO), Near-Packaged Optics (NPO), silicon photonics, pluggable optics, advanced packaging, or rack-scale fiber management.
Optical Engineering, Standards, and Validation
- Experience with optical engineering concepts, testing procedures, laboratory tools, analysis methods, or relevant industry standards.
- Experience testing or validating active or passive fiber-optic components and end-to-end fiber links.
- Familiarity with relevant standards or specifications, such as IEEE Ethernet, OIF, or CMIS.
Datacenter & Manufacturing
- Experience developing high-density fiber infrastructure, including fiber shuffle solutions, patch panels, connectors, cable assemblies, and rack-scale optical systems.
- Experience with hyperscale datacenter deployment, optical manufacturing processes, and ODM, contract manufacturer, and supplier ecosystems.
- Experience managing optical or networking products through EVT, DVT, PVT, qualification, and production ramp.
Software & Automation
- Experience with Linux environments and automation frameworks.
- Experience developing telemetry, diagnostics, validation, and qualification tooling.
- Familiarity with scripting and data analysis environments.
#azure #AI/ML #Optical Networking Hardware
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.
