Join the Windows AI Platform Engineering team and contribute to the future of AI experiences on Windows. We develop the core platform, APIs, evaluation tools, and developer resources that empower Microsoft and external developers to build intelligent, reliable, and engaging AI-powered features across the Windows ecosystem.

Our platform supports the creation of high-quality, dependable, and responsible AI applications on a wide range of devices. It integrates model deployment, developer kits, quality assessment, runtime management, monitoring, and production engineering. We transform cutting-edge AI capabilities into scalable building blocks that operate efficiently at Windows scale.

Lead the architecture, design, and implementation of critical Windows AI platform components, services, APIs, SDKs, and developer tools. Translate complex product and platform requirements into clear technical roadmaps and engineering strategies.

Define scalable patterns for model management, inference, orchestration, and lifecycle support. Design architectures that scale across diverse Windows devices and scenarios while ensuring API consistency, backward compatibility, and cost-effectiveness.

Drive comprehensive quality strategies, including automated testing, performance tuning, reliability, security, privacy, and responsible AI validation. Lead technical investigations, guiding prototypes from concept to production-ready features. Own system observability, incident response, and continuous improvement initiatives.

A Bachelor's Degree in Computer Science or a related technical field, coupled with 8+ years of professional software development experience, is required. Proficiency in programming languages like C++, C#, or Python is essential, alongside a solid understanding of software design principles, data structures, algorithms, and version control.

Demonstrated experience in designing and delivering complex production software, developer platforms, or distributed systems is crucial. The ability to lead technical execution across multiple teams and navigate ambiguity is highly valued.

Preferred qualifications include deep expertise in AI/ML platforms, model serving, inference systems, or AI developer tooling. Experience with cloud technologies like Azure, distributed systems, CI/CD pipelines, and Windows development technologies is also beneficial.