Principal Optical Network System Engineer

Microsoft•Redmond, WA

1d•$142,800 - $304,200

About The Position

Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission. Microsoft's Hardware Systems organization is developing AI-native silicon and system-level solutions to power the next generation of frontier AI models. The platform combines custom accelerators, advanced networking technologies, large-scale distributed infrastructure, and cloud-scale software to deliver industry-leading AI training and inference capabilities. The Platform Systems Engineering (PSE) team is seeking a Principal Optical Network System Engineer to lead the architecture, engineering, productization, and deployment of optical interconnect solutions and rack-scale fiber management for next-generation AI and cloud infrastructure. This role will own the product development lifecycle from early concept and technology selection through qualification, manufacturing readiness, and large-scale production deployment. As the Principal Optical Network System Engineer, you will work across silicon, systems, networking, platform architecture, datacenter engineering, manufacturing, and external ecosystem partners to translate platform requirements into scalable optical products. You will define technical requirements and roadmaps, drive design tradeoffs, lead cross-functional execution, and ensure that optical links, modules, cabling, connectors, and rack-level fiber architectures meet performance, power, reliability, serviceability, cost, and deployment goals. You may bring deep knowledge of optical systems along with experience in areas such as product architecture, technology development, ecosystem collaboration, or engineering execution. They can influence platform-level decisions across multiple generations of AI infrastructure, align diverse engineering teams and suppliers, manage technical risk, and deliver innovative optical technologies from concept to production at cloud scale. This is a unique opportunity to shape the optical connectivity foundation for Microsoft's future AI systems. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

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.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

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.
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.
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.
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.
Experience with Linux environments and automation frameworks.
Experience developing telemetry, diagnostics, validation, and qualification tooling.
Familiarity with scripting and data analysis environments.

Responsibilities

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.
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.
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.
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.
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.
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.
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.