The Principal Software Engineer, Storage Infrastructure role is part of the Foundry and Inference Training (FIT) team at Microsoft AI Infrastructure. This team focuses on building platforms and systems for large-scale AI training and inference on Azure. The role involves designing, building, and operating storage platforms while collaborating with various teams to enhance storage performance and reliability. This position offers opportunities for technical leadership and shaping platform architecture in a dynamic environment.

• 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++, C#, Java, JavaScript, or Python.
• Ability to meet Microsoft, customer and/or government security screening requirements.
• 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++, C#, Java, JavaScript, 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++, C#, Java, JavaScript, or Python.
• 5+ years of experience designing, building, or operating distributed systems, storage systems, file systems, databases, or cloud infrastructure services.

• Design, build, and evolve distributed storage systems and file systems for cloud-scale AI training and inference workloads.
• Architect and operationalize storage stacks for large Kubernetes clusters, optimizing data access, throughput, latency, scalability, and reliability for GPU-accelerated workloads.
• Design storage and key-value caching architectures that improve LLM inference latency, throughput, resource utilization, and cost efficiency.
• Improve durability, availability, performance, and operational maturity through automation, observability, diagnostics, incident response, and resiliency engineering.
• Analyze complex cross-layer production issues, identify root causes, and implement durable improvements across storage, compute, networking, and runtime components.
• Partner with infrastructure and machine learning platform teams to deliver end-to-end capabilities for foundation-model pre-training, post-training, fine-tuning, and inference.
• Lead architecture reviews, influence long-term storage strategy, mentor engineers, and establish engineering practices for secure and reliable cloud services.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.