Join Microsoft's Specialized Cloud team and drive innovation in Azure's latest offerings for edge computing. Empower global customers by solving real-world challenges with intelligent cloud solutions.

This role offers a unique opportunity to shape the future of cloud and edge computing, pushing technological boundaries to deliver secure, reliable, and scalable solutions. We are a team of self-driven individuals passionate about creating elegant solutions and fostering a culture of growth, respect, and accountability.

Embrace challenges and contribute to a world-class team committed to empowering every person and organization to achieve more. If you have a passion for writing high-quality code and leveraging AI for development, we encourage you to apply.

Architect and integrate robust storage and file system components for Windows and Linux.

Develop resilient clustering and virtualization solutions across Windows and Linux platforms.

Design scalable, distributed cloud services for managing edge infrastructure, including clustering, hypervisors, and storage.

Lead by example, elevate team standards, and cultivate a collaborative, data-driven environment.

Analyze and debug complex issues, articulate findings clearly, and integrate AI into problem-solving.

Collaborate effectively with cross-functional product teams to manage dependencies and enhance engineering capabilities.

A strong foundation with over 10 years in software development, focusing on distributed systems and operating systems, is essential. A Bachelor's or Master's degree in Computer Science or a related field is required.

Demonstrated expertise with 5+ years in designing, developing, deploying, and monitoring failover clustering, resilient storage, and Hyper-V management.

Proficiency in working with SAN storage (iSCSI and FC) and troubleshooting intricate interoperability issues is crucial.

Exceptional programming skills in C#, Rust, Java, C/C++, coupled with strong debugging, design, and problem-solving abilities are highly desired. A deep understanding of data structures and algorithms for performance, scalability, and reliability is key.

Experience with AI/ML and LLMs is a significant advantage. Backgrounds in kernel and device driver development, as well as expertise in Windows Server technologies like Storage Spaces and Software Defined Storage, are highly valued. Familiarity with storage and file systems in Kubernetes environments is also beneficial.