Principal AI Back-End Network Systems Lead
$142.8k - $304.2k/yr
Senior
Bachelor's, Master's
Redmond, WA, USA+2 moreMore locations: Hillsboro, OR, USA | Mountain View, CA, USA
In Person
Hardware EngineeringHardware Systems Integration
Company Historically Provides H1B Sponsorship
About the job
Requirements
- A master's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a related field and 7+ years of technical engineering experience; or a bachelor's degree in one of those fields and 8+ years of technical engineering experience; or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
- Preferred: A bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field and 10+ years of relevant experience in networking, distributed systems, accelerator platforms, or cloud infrastructure, or equivalent experience.
- Preferred: 6+ years of experience designing, developing, integrating, or validating networking for AI/ML, HPC, accelerator, or large-scale cloud systems.
- Preferred: Deep hands-on expertise in at least one AI/ML networking domain, such as scale-up interconnects and silicon/SerDes/PHY, electrical or optical connectivity, switch systems, scale-out Ethernet/RDMA fabrics, transport/congestion control, collective communication, or workload/fabric performance.
- Preferred: Demonstrated experience leading a complex hardware/software product or subsystem through requirements, architecture, development, integration, validation, and production deployment.
- Preferred: Experience architecting or delivering both scale-up and scale-out networks for large AI training or inference systems.
- Preferred: Experience with high-speed electrical and optical technologies, SerDes/PHY, FEC, signal integrity, link training, retimers, cable/backplane design, pluggable or co-packaged optics, and 400G/800G or faster links.
- Preferred: Experience with switch ASICs and systems, NICs/DPUs, Ethernet, RDMA/RoCE, routing, QoS, ECN/PFC/DCQCN or related congestion-control methods, SONiC/Linux networking, and network operating systems.
- Preferred: Understanding of collective communication libraries and operations, distributed training parallelism, AI workload traffic patterns, and workload-driven network optimization.
- Preferred: Experience with network and system modeling, simulation, emulation, performance analysis, topology studies, traffic generation, or collective/workload scaling analysis.
- Preferred: Experience developing automated validation, stress, reliability, interoperability, telemetry, diagnostics, observability, and fleet-health frameworks.
- Preferred: Track record of system bring-up and cross-layer debugging from physical links through protocol, runtime, collectives, and application behavior.
- Preferred: Experience driving manufacturing readiness, supplier/partner execution, datacenter deployment, serviceability, and fleet operations for hardware-intensive products.
- Preferred: Strong product judgment, technical leadership, collaboration, written communication, and executive presentation skills.
Responsibilities
- Own the Back End Network product definition and execution plan across scale-up and scale-out, from customer/workload needs and product requirements through architecture, development, qualification, deployment, and fleet learning.
- Translate AI training and inference requirements into measurable system targets for bandwidth, latency, scale, collective efficiency, reliability, availability, serviceability, power, thermal behavior, cost, security, and schedule.
- Make and drive cross-system architecture decisions, interface contracts, feature priorities, and risk tradeoffs; maintain clear ownership, milestones, entry/exit criteria, and product readiness metrics.
- Lead NUDD (new, unique, different, and difficult) technology assessments, prototypes, make/buy/partner decisions, and mitigation plans for the highest product risks.
- Lead architecture and integration across accelerator and networking silicon, NICs/DPUs, PHYs/retimers, switch ASICs, switches, cables/backplanes, optics, and fabric topology.
- Define scalable scale-up and scale-out architectures, including topology, radix, reach, link speeds, routing, path diversity, oversubscription, failure domains, and resiliency.
- Drive silicon, board, switch, firmware, network operating system, and fabric requirements so that components operate as one high-performance and serviceable product.
- Partner with silicon, switch, optical, cable, connector, system, manufacturing, and supplier teams to deliver designs from concept through production and datacenter integration.
- Oversee electrical and optical technologies for high-speed links, including signal integrity, SerDes/PHY, link training, FEC, reach, power, thermal, mechanical, manufacturability, and interoperability tradeoffs.
- Drive end-to-end behavior across the relevant OSI layers—physical, data link, network, and transport—and the system/runtime interfaces above them.
- Define and validate Ethernet/RDMA or other scale-up/scale-out protocol behavior, including flow control, congestion control, QoS, routing, packet loss/recovery, telemetry, and security.
- Ensure hardware, firmware, drivers, network operating systems, management software, orchestration, and datacenter operations are aligned to common specifications and concepts of operation.
- Connect network architecture to distributed AI workloads, parallelism strategies, traffic patterns, and collective operations such as all-reduce, all-gather, reduce-scatter, and all-to-all.
- Establish analytical and simulation models for topology, bandwidth, latency, congestion, failure behavior, collective efficiency, workload scaling, power, and cost.
- Use models, emulation, prototypes, and lab/fleet data to predict bottlenecks, guide design choices, set performance budgets, and validate architectural assumptions.
- Partner with workload, collective-communication, compiler/runtime, and application teams to co-optimize the network and improve job completion time and cluster efficiency.
- Own the end-to-end validation strategy covering functionality, interoperability, performance, scale, stress, resiliency, reliability, security, serviceability, and upgrade/recovery behavior.
- Lead bring-up and root-cause analysis across silicon, electrical/optical links, switch, fabric, protocol, system software, collective, and workload layers using telemetry, packet captures, counters, diagnostics, and lab characterization.
- Define production qualification, manufacturing test, deployment, monitoring, rollback, and fleet-health requirements; use operational learning to drive corrective actions and next-generation improvements.
- Drive product readiness reviews and ensure the solution can be safely and repeatably deployed, operated, serviced, and scaled in hyperscale datacenters.
- Create clarity and technical alignment across architecture, silicon, hardware, optics, firmware, networking, software, validation, manufacturing, datacenter, and workload teams.
- Influence internal roadmaps and external partners, including silicon, switch, optical, interconnect, ODM/OEM, and open-source ecosystems; resolve cross-team gaps and ambiguous ownership.
- Communicate product status, architectural decisions, risks, tradeoffs, and executive asks clearly while mentoring engineers and raising the quality of end-to-end systems engineering.
About the company
Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.
Company Size
10,001+
Company Stage
IPO
Headquarters
Redmond, Washington
Founded
1975
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Simplify's Take
What believers are saying
- US corporate staff receive education support: eligible, approved graduate coursework qualifies for up to $10,000 annually.
- Cloud demand expands: July 2026 results showed Azure and other cloud services revenue grew 43% year-over-year in fiscal Q4.
- Investment has an earnings cushion: July 2026 results reported $155.2 billion consolidated operating profit for fiscal 2026.
What critics are saying
- Performance reviews include security: every Microsoft employee must discuss their security contribution with their manager.
- Office flexibility depends on the role: Microsoft's postings specify requirements ranging from fully remote to fully on-site.
- Cloud capacity faces local limits: Microsoft describes power-grid delays and water constraints affecting US datacenter expansion.
What makes Microsoft unique
- Hybrid customers stay within reach: Azure Arc manages servers across customer datacenters and competing clouds.
- Developer reach extends beyond Azure: Microsoft's GitHub hosts code collaboration alongside AI coding tools.
- Professional data widens its business: Microsoft owns LinkedIn's recruiting, advertising and workplace-learning network.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- 401(k) Company Match
- Professional Development Budget
- Conference Attendance Budget
- Flexible Work Hours
- Remote Work Options