Note: The job is a remote job and is open to candidates in USA. Microsoft is seeking a Principal Software Engineer for its Azure Blob Storage team. The role leads the design and delivery of distributed storage systems optimized for AI and machine-learning workloads, shaping architecture and driving development, testing, deployment, and technical innovation at hyperscale.

Responsibilities

• Design and deliver next-generation distributed storage systems optimized for AI/ML workloads, from training to inferencing
• Provide technical leadership across architecture, development, testing, and deployment at hyperscale
• Drive innovations in scalability, performance, security, and efficiency to meet the demands of zettabyte-scale storage
• Collaborate with cross-functional teams from AI researchers to cloud infrastructure engineers to ensure storage meets the needs of cutting-edge AI workloads
• Mentor and guide other engineers, fostering a culture of technical excellence, innovation, and collaboration
• Continuously evaluate emerging technologies and trends to anticipate the future of AI-native storage

Skills

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, or Python + OR equivalent experience
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
• Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, or Python + OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, or Python + OR equivalent experience
• Passion for distributed systems, large-scale storage, and solving complex systems problems
• Storage system internals in areas such as availability, remote replication, durability schemes, and high-performance I/O
• Database internals, indexing and search techniques, caching and data placement strategies
• Metadata and namespace management at scale

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