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Are you interested in leading a team to build a world-class deployment system to manage hyperscale environments? Do you want to revolutionize application and infrastructure deployment with simplification? Are you looking to use AI at scale to transform and optimize deployment at scale? Do you want to have direct and immediate impact on a large number of M365 services used by millions of people across the world, hundreds of thousands of commercial organizations, and government agencies? Do you want to be part of a fun and inclusive work environment? We are looking for a Principal Software Engineer to join our team. On the Substrate Deployment Team, we are responsible for deploying changes to hundreds of thousands of servers across all our datacenters. Our team builds the platform that not only provides a scalable, efficient, and cost-effective deployment solution for high-scale services, but also leverages AI-driven innovation to improve deployment reliability, automation, and operational excellence. We manage infrastructure throughout the application lifecycle to make the experience seamless for our customers.
Job Responsibility
Work with engineers, product managers, and partner teams to deliver experiences with the right overall design and architecture, leveraging AI where it can meaningfully improve deployment efficiency, reliability, and customer outcomes
Provide mentorship and coaching to engineers both in, and beyond, your team, including the adoption of modern AI-powered development practices and tools
Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing
Drive innovation through automation and AI-powered solutions to improve deployment intelligence, operational efficiency, and service reliability at hyperscale
Ensure your team delivers clean, well-thought-out code with an emphasis on quality, performance, simplicity, durability, scalability, maintainability, and effective use of AI-assisted engineering practices.
Requirements
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 OR equivalent experience
Preferred: 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 OR equivalent experience
Proficiency in AI-native development
Fundamentals in data structures, algorithms, object-oriented design, and scalable systems
Experience building, testing, debugging, and maintaining production-quality software
Problem-solving and technical judgment skills
Experience with cloud platforms and distributed/service-oriented architecture
Experience with reliability, monitoring, and performance optimization practices
Experience in driving AI (LLM/ML) based engineering solution
Nice to have
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 OR equivalent experience
Proficiency in AI-native development
Fundamentals in data structures, algorithms, object-oriented design, and scalable systems
Experience building, testing, debugging, and maintaining production-quality software
Problem-solving and technical judgment skills
Experience with cloud platforms and distributed/service-oriented architecture
Experience with reliability, monitoring, and performance optimization practices
Experience in driving AI (LLM/ML) based engineering solution