Principal Software Engineer

• Lead technical strategy for enabling and optimizing frontier-scale AI models across Microsoft AI accelerators and cloud-scale AI infrastructure.
• Architect and optimize AI systems across hardware compilers kernels frameworks runtimes and distributed infrastructure to improve training and inference performance.
• Partner with hardware architecture teams on hardware-software co-design influencing accelerator features memory systems interconnects execution models and future silicon roadmaps.
• Drive performance optimization across kernels communication memory movement quantization attention mixture-of-experts (MoE) and other critical AI workloads.
• Architect distributed training and inference solutions spanning large accelerator clusters including parallelism communication memory management and scaling strategies.
• Drive model enablement and performance improvements across AI frameworks and inference technologies such as PyTorch Triton vLLM SGLang and related ecosystems.
• Lead architecture reviews and complex cross-organization technical initiatives build alignment across engineering teams mentor engineers and provide technical recommendations that inform Microsofts long-term AI infrastructure strategy.

• Ability to meet Microsoft customer and/or government security screening requirements including Microsoft Cloud Background Check requirements.

• 7 years of experience developing and optimizing high-performance AI systems kernels or accelerator software using CUDA ROCm Triton or similar programming models.
• Deep experience optimizing large-scale AI workloads including attention mixture-of-experts (MoE) quantization FP8 KV-cache management memory efficiency or related techniques.
• Experience enabling and optimizing large language reasoning multimodal or other foundation models on AI accelerators.
• Experience designing distributed training or inference systems using techniques such as tensor pipeline expert or sequence parallelism.
• Deep knowledge of AI frameworks such as PyTorch and experience optimizing production-scale training or inference workloads.
• Demonstrated experience leading complex technical initiatives across multiple engineering organizations and influencing technical strategy beyond immediate team boundaries.
• Publications patents open-source contributions or other recognized contributions in AI systems distributed computing machine learning infrastructure or hardware acceleration.

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142800 - $274800 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 $188000 - $304200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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.

Required Experience:

IC