微软Principal Software Engineer
任职要求
Required Qualifications: • 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. • Proven track record in designing and managing large-scale distributed systems. • Strong proficiency in cloud infrastructure and modern web technologies. • Experience in building AI-powered applications is a significant advantage. • Outstanding leadership capabilities combined with excellent communication skills. Preferred / Additional Qualifications: • 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 i…
工作职责
• Own the design and implementation of core infrastructure components, ensuring scalability, security, and high performance across systems. • Lead architectural decisions, set engineering standards, and drive long-term technical strategy for complex solutions. • Produce and review high-quality, secure, and maintainable code while championing best practices and modern patterns, including AI-driven approaches. • Mentor engineers across teams, fostering growth in coding, design, testing, and operational excellence. • Define and enforce robust test strategies, integrate automation, and ensure security and reliability in all deliverables. • Oversee telemetry, incident response, and operational readiness to improve system stability and supportability. • Collaborate with stakeholders to validate requirements, incorporate feedback, and uphold compliance, privacy, and accessibility standards.
- Keep up to date with and utilize the latest developments in LLM system optimization.- Take the lead in designing innovative system optimization solutions for internal LLM workloads.- Optimize LLM inference workloads through innovative kernel, algorithm, scheduling, and parallelization technologies.- Continuously develop and maintain internal LLM inference infrastructure.- Discover new LLM system optimization needs and innovations.
•  Work with a team of passionate engineers to deliver success for customers•  Design, implement, test, and operate data services.•  Release features on time, with high quality, meeting functional, performance, scalability, and compliance requirements.•  Drive quality right from the design phase, incorporating best practices and engineering for testability.•  Solve problems relating to mission critical services and create solutions to prevent problem recurrence.•  Participate in product live site and operations.
• Lead the technical direction and vision for the architecture, design, and the implementation of our infrastructure on Azure that scales to provision, manage, and monitor health of millions of cloud-based virtual devices. • Mentor and help grow a team of talented, diverse software engineers. • Work across organizations, collaborating with internal partner teams such as Azure Compute, Core OS, Microsoft Security and Identity team, and others. • Raise the technical bar, maintain a data and results driven culture, and nurture a high-performance team to build world-class experiences for W365 ITPros, partners, and operations teams. • Get to extend your knowledge of cloud computing, hypervisors, desktop virtualization, streaming technologies, and other technical areas including cloud-based management suites. • Be part of a team designing fundamental capabilities involving device management, computing, storage, networking, and streaming protocols (such as Remote Desktop Protocol) for our core products to enhance the value to our customer base. • Be a part of an agile team working with experienced engineers and product managers that behave more like a technology startup.
Architect, build, and optimize secure and performant AI platform services that power Microsoft Copilot and other next-generation AI scenarios. Provide technical leadership across teams to define long-term architectural direction and drive engineering excellence. Collaborate with infrastructure, platform, product, and research teams to design and deliver scalable, production-grade AI services. Write high-quality, well-tested, secure, and maintainable code and promote high standards across the team. Tackle technically ambiguous or cross-boundary problems, remove roadblocks, and drive delivery across multiple teams or organizations. Lead technical design discussions, mentor senior engineers, and foster a strong engineering culture within the team. Embody Microsoft’s Culture and Values, and help shape the direction of the engineering team and broader organization.