Senior AI Software Architect

Do 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 seeking a Senior AI Software Architect to join the AI Systems Architecture (ASA) group, where we define, validate, and optimize Microsoft’s next-generation AI systems across hardware, software, and cloud-scale deployment boundaries. In this role, you will drive software bring-up, performance analysis, and optimization for multiple generations of AI accelerators, working across the full stack from low-level kernels and compiler/runtime integration to distributed training, inference serving, networking, and fleet-scale system behavior. You will develop strategies that improve the correctness, efficiency, reliability, and scalability of real-world AI workloads, including deep analysis of training and inference runs to validate numerical behavior, identify bottlenecks, and guide architectural tradeoffs. You will collaborate closely with architecture, microarchitecture, compiler, runtime, networking, and systems teams to translate workload insights into practical system designs that enable efficient large-scale AI deployment. 

RESPONSIBILITIES:   

• Lead end-to-end software architecture and performance optimization for AI accelerator platforms. 

• Prototype and validate software capabilities across kernels, compiler and runtime layers, distributed training and inference frameworks, and serving infrastructure. 

• Analyze workload behavior at scale to identify performance bottlenecks, numerical correctness issues, and system-level efficiency opportunities. 

• Use workload insights to guide hardware-software co-design decisions across architecture, silicon, systems software, networking, and product teams. 

• Define requirements, evaluate tradeoffs, and deliver practical solutions for production-scale AI systems.