Principal AI Architect
 Microsoft | |
 United States, California, Mountain View | |
 Oct 31, 2025 | |
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OverviewDo you want to be at the forefront of innovating the latest hardware designs to propel Microsoft's cloud growth? Are you seeking a unique career opportunity that combines technical capabilities, cross-team collaboration with business insight and strategy?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 achieve 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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.Join the Systems Planning and Architecture (SPARC) team within Microsoft's Azure Hardware Systems and Infrastructure (AHSI) organization, the team behind Microsoft's expanding Cloud Infrastructure and for powering Microsoft's "Intelligent Cloud" mission. Microsoft delivers more than 200 online services to more than one billion individuals worldwide, and AHSI is the team behind our expanding cloud infrastructure. We deliver the core infrastructure and foundational technologies for Microsoft's cloud businesses including Microsoft Azure, Bing, MSN, Office 365, OneDrive, Skype, Teams and Xbox Live. We are looking for a Principal AI Architect to join our team!
ResponsibilitiesModel Bring-Up & CharacterizationLead the bring-up and functional validation of LLMs on custom AI accelerators and GPUs Develop and maintain detailed performance characterizations across compute, memory, and interconnect domains.Instrument and profile end-to-end training and inference workloads to identify scaling inefficiencies and performance gaps.Hardware/Software/Model Co-Design Partner with silicon and system architects, compiler/runtime engineers, and model researchers to define co-design strategies that maximize efficiency and utilization.Drive studies and experiments across quantization formats, tensor parallelism, activation checkpointing, memory layouts, and communication topologies.Performance Optimization-Analyze kernel- and system-level traces to identify limiting factors in compute, memory, and interconnect.Propose and implement optimizations in scheduling, fusion, and data movement to improve throughput and power efficiency.Guide runtime and compiler improvements informed by workload analysis.Cross-Functional LeadershipCollaborate with teams across Azure ML, DeepSpeed, and Maia hardware programs to deliver production-grade AI infrastructurePresent architectural findings and recommendations to senior engineering leadership.Mentor and technically guide engineers working in performance, compiler, and system bring-up domains. | |