The role is for a Senior or Principal Software Engineer in the AI Infrastructure Engineering Systems team at Microsoft. This team focuses on building the cloud platform and engineering infrastructure that supports AI services at scale. The engineer will be responsible for designing and improving large-scale distributed systems while collaborating with various teams. The position emphasizes navigating complex infrastructure challenges and delivering reliable solutions.

• Bachelor's Degree in Computer Science or related technical field AND 4+ 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 6+ 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 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.
• Experience architecting, building, and operating large-scale distributed systems.
• Experience developing backend services, databases, data infrastructure, storage systems, streaming platforms, or network infrastructure.
• Experience with cloud platforms, container orchestration, or distributed data-processing technologies.
• Experience influencing open-source projects or participating in open-source project management and governance.
• Demonstrated ability to independently navigate ambiguous technical challenges, define problems, evaluate architectural trade-offs, and deliver solutions in complex, evolving environments.
• Familiarity with AI/ML infrastructure concepts, such as model inference, GPU computing, model serving, or distributed training.

• Own technical strategy and lead architecture discussions for broad or complex infrastructure requirements.
• Design, implement, and optimize large-scale distributed systems for performance, scalability, resiliency, security, privacy, compliance, and cost efficiency.
• Improve system observability and understandability through metrics, logging, telemetry, and tools that support developer productivity and reliable operation.
• Independently create test strategies, incorporate security testing, improve test coverage, and address difficult-to-test areas through design or rearchitecture.
• Diagnose production issues, conduct incident retrospectives, implement preventive actions, and drive automation across production deployment and routine operations.
• Participate in and influence relevant open-source projects, and identify or build reusable internal and open-source tools that improve engineering effectiveness.
• Communicate with stakeholders and partner teams, resolve cross-team dependencies, mentor engineers, and iteratively deliver software at scale.
• Collaborate across infrastructure and AI teams to improve the performance, efficiency, and reliability of large-scale AI workloads.
• Drive complex, ambiguous infrastructure initiatives from problem discovery through architecture, implementation, and production.

• 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.