Lead AI Software Architect
 Microsoft | |
 United States, Washington, Redmond | |
 Sep 04, 2025 | |
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OverviewDo you want to be at the forefront of innovating the latest Inference systems 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 Strategic 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 Lead AI Software Architect to join our team!
ResponsibilitiesLead the SW architectural design, development, and deployment of the future AI inference infrastructure optimized for Microsoft's AI cloud.Collaborate closely with hardware architecture, compiler, systems, simulation/perf optimization to ensure seamless integration and optimized performance.Define and execute strategies for inference , cost optimizations, workload balancing, and memory optimization.Mentor and guide the software engineering team, setting clear technical directions and providing architectural oversight.Evaluate, select, and integrate third-party libraries and open-source frameworks (e.g., TensorRT, TVM, PyTorch, ONNX) for optimized inference performance.Act as a technical liaison between hardware engineers and software teams to communicate requirements, constraints, and opportunities for co-design.Identify performance bottlenecks and opportunities to intersect future hardware and system roadmap planning, influencing strategic direction.Ensure robust software quality and implement best practices for software engineering, testing, and continuous integration. | |