Job description

Overview 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 engineers to help achieve that mission. As Microsoft's cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the Cloud Hardware Systems Engineering (CHSE) team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure. We are looking for a Principal AI Network Architect to join the team. #SCHIE Responsibilities • Define the long-term architecture and technology roadmap for Microsoft's AI scale-up networking systems. • Architect next-generation scale-up switches, including system architecture, switch topology, ASIC selection, radix planning, electrical and optical interconnect strategies. • Define network architectures for AI clusters, racks, pods, and multi-rack scale-up domains. • Drive architecture tradeoff analysis across performance, scalability, reliability, power, cost, serviceability, and operational efficiency. • Define scale-up network requirements based on AI training, inference, and emerging workload demands. • Lead architecture studies for switch silicon, optics, interconnect technologies, control planes, and AI fabrics. • Define switch system requirements, architecture specifications, and design guidelines for future Microsoft AI platforms. • Drive architecture decisions for scale-up and scale-out networks, including topology, oversubscription, resiliency, fault tolerance, and workload placement optimization. • Partner with system, silicon, optics, software, firmware, and operations teams to co-design end-to-end AI infrastructure solutions. • Develop performance, capacity, reliability, and TCO models to evaluate architecture alternatives and guide investment decisions. • Evaluate emerging networking technologies and influence industry roadmaps across switch silicon, optics, and networking ecosystems. • Provide technical direction and architectural guidance to switch development teams, ODM/JDM partners, and platform engineering organizations. Qualifications Required 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 Other Requirements: • Ability to meet Microsoft, customer, and/or government security screening requirements is required for this role. These requirements include, but are not limited to, the following specialized security screening: • Microsoft Cloud Background Check. This position is required to pass the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter. • This role will require access to information that is controlled for export under export control regulations, potentially under the U.S. International Traffic in Arms Regulations or Export Administration Regulations, the EU Dual Use Regulation, and/or other export control regulations.  As a condition of employment, the successful candidate will be required to provide either proof of their country of citizenship or proof of their U.S. permanent residency or other protected status (e.g., under 8 U.S.C. 1324b(a)(3)) for assessment of eligibility to access the export-controlled information. To meet this legal requirement, and as a condition of employment, the successful candidate’s citizenship will be verified with a valid passport. Lawful permanent residents, refugees, and asylees may verify status using other documents, where applicable. Preferred Qualifications: • BS / MS in Electrical/Computer Engineering or equivalent industry experience. • 10+ years of relevant experience in system (compute, storage, networking, and/or accelerator) level design and/or implementation across the hardware development lifecycle. • 10+ years of hands-on experience in server hardware architecture, design, and development with solid understanding of hardware, firmware, and Operating System (OS).  • Proven experience delivering AI and GPU-based systems to production. • 10+ years of experience in networking, distributed systems, AI infrastructure, or large-scale system architecture. • Deep understanding of AI scale-up and scale-out networking architectures. • Experience architecting high-performance network switches and large-scale switching systems. • Knowledge of Ethernet, RDMA/RoCE, SONiC, network operating systems, and control plane architectures. • Experience with switch ASICs, SerDes technologies, retimers, PHYs, and high-speed electrical interconnects. • Experience with optical networking technologies including OCI, XPO, CPO, OBO, and optical fabrics. • Experience performing architecture tradeoff analysis involving performance, power, cost, reliability, and scalability. • Familiarity with AI workloads, collective communication patterns, distributed training, and inference systems. • Proven system-level architecture skills spanning networking, compute, power, thermal, and rack integration. • 10+ years of experience in network switch system-level design, spanning all phases of product development — from concept through production release. • Proven expertise in network switch architecture and development. • Demonstrated leadership in network switch design reviews, driving cross-functional alignment across hardware, firmware, software, and infrastructure teams. 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: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

We are looking for a Principal AI Network Architect to join the team.
Define the long-term architecture and technology roadmap for Microsoft's AI scale-up networking systems.
Architect next-generation scale-up switches, including system architecture, switch topology, ASIC selection, radix planning, electrical and optical interconnect strategies.
Define network architectures for AI clusters, racks, pods, and multi-rack scale-up domains.
Drive architecture tradeoff analysis across performance, scalability, reliability, power, cost, serviceability, and operational efficiency.
Define scale-up network requirements based on AI training, inference, and emerging workload demands.
Lead architecture studies for switch silicon, optics, interconnect technologies, control planes, and AI fabrics.
Define switch system requirements, architecture specifications, and design guidelines for future Microsoft AI platforms.
Drive architecture decisions for scale-up and scale-out networks, including topology, oversubscription, resiliency, fault tolerance, and workload placement optimization.
Partner with system, silicon, optics, software, firmware, and operations teams to co-design end-to-end AI infrastructure solutions.
Develop performance, capacity, reliability, and TCO models to evaluate architecture alternatives and guide investment decisions.
Evaluate emerging networking technologies and influence industry roadmaps across switch silicon, optics, and networking ecosystems.

Nice-to-haves

BS / MS in Electrical/Computer Engineering or equivalent industry experience.
Proven experience delivering AI and GPU-based systems to production.
Deep understanding of AI scale-up and scale-out networking architectures.
Experience architecting high-performance network switches and large-scale switching systems.
Knowledge of Ethernet, RDMA/RoCE, SONiC, network operating systems, and control plane architectures.
Experience with switch ASICs, SerDes technologies, retimers, PHYs, and high-speed electrical interconnects.
Experience with optical networking technologies including OCI, XPO, CPO, OBO, and optical fabrics.
Experience performing architecture tradeoff analysis involving performance, power, cost, reliability, and scalability.
Familiarity with AI workloads, collective communication patterns, distributed training, and inference systems.
Proven system-level architecture skills spanning networking, compute, power, thermal, and rack integration.
Proven expertise in network switch architecture and development.
Demonstrated leadership in network switch design reviews, driving cross-functional alignment across hardware, firmware, software, and infrastructure teams.

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Keywords to mirror

azureai

Platform: eightfold
Effort: medium

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