Note: The job is a remote job and is open to candidates in USA. Microsoft is building Azure Storage as a foundational cloud platform for AI, analytics, enterprise workloads, and intelligent services. The Principal Software Engineer will lead the design and evolution of hyperscale storage control plane capabilities, drive distributed systems and AI-assisted engineering innovations, shape technical strategy, and own the reliability and operation of critical service components.
Responsibilities
- Lead the design and evolution of Azure Storage capabilities that power the next generation of AI platforms, autonomous AI agents, and hyperscale cloud services. Architect and deliver scalable control plane and management plane services that enable AI-scale workloads to provision, manage, and access storage resources with industry-leading performance, reliability, and efficiency
- Drive innovations in distributed systems, intelligent automation, and resource orchestration to eliminate bottlenecks and unlock the next order of magnitude of platform scale. Partner with engineers, architects, product managers, and AI platform teams across Microsoft to define technical strategy and deliver foundational capabilities that accelerate AI innovation
- Leverage cutting-edge AI engineering tools, agentic workflows, and code-generation technologies to accelerate development velocity, improve code quality, and enhance engineering productivity across the organization. Explore and implement AI-assisted software development practices, including automated code generation, test creation, debugging, design validation, and operational troubleshooting at cloud scale
- Help define how AI transforms software engineering at hyperscale, pioneering new approaches that combine human expertise with intelligent agents to build and operate the next generation of cloud infrastructure. Partner with AI platform teams to identify opportunities where intelligent agents can automate engineering, deployment, reliability, and operational workflows across Azure Storage
- Influence the long-term architecture and technical roadmap for Azure Storage, helping shape the storage foundation behind training, inference, and agentic AI workloads. Leverage deep expertise in cloud infrastructure and distributed systems to solve complex challenges in scalability, resiliency, availability, and operational excellence at global scale
- Serve as a Designated Responsible Individual (DRI) for critical service components, driving end-to-end ownership of system health, reliability, performance, and incident response
Skills
- Bachelor's Degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C#, C++, Java, or other languages
- + OR equivalent experience
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
- Master's Degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C#, C++, Java, or other languages
- + OR Bachelor's Degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C#, C++, Java, or other languages
- + OR equivalent experience
- 7+ years designing and operating hyperscale cloud platforms, storage services, or distributed systems with a focus on scalability, reliability, and performance
- Building distributed storage systems, databases, or infrastructure services at scale
- Designing platforms or services that power AI training, inference, retrieval, reasoning, or agent orchestration workloads
- Applying AI-powered engineering practices, including code-generation tools, agentic workflows, AI-assisted development, automated testing, debugging, and operational troubleshooting
- Building platforms or infrastructure that support AI workloads, large-scale inference systems, autonomous agents, or data-intensive applications
- Championing AI-first engineering practices and influencing engineering transformation across teams or organizations
- Proven track record of operating highly available cloud services with stringent reliability requirements
- Expertise in AI-enabled software engineering, including agentic development workflows, LLM-powered coding assistants, automated code generation, and intelligent operational tooling
- Proven technical leadership driving architecture, strategy, and execution for large-scale cloud services and distributed systems
- Passion for leveraging AI to transform software engineering productivity, quality, and operational excellence at scale
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