微软Principal Software Engineer (MAI Copilot)
任职要求
Bachelor’s degree in Computer Science or related technical field AND 10+ years of technical engineering experience, including hands-on coding in languages such as C#, C++, Python, Go, Rust, or Java OR equivalent practical experience in building distributed systems and core platforms. 8+ years of experience designing and building scalable services on public cloud platforms such as Azure, AWS, or GCP. Deep experience with distributed systems, large-scale infrastructure, and end-to-end systems architecture, including networking, containers, and data pipelines. Demonstrated technical influence across teams, with a proven ability to define strategy, make critical design tradeoffs, and drive alignment in complex, multi-stakeholder environments. Shape Preferred Qualifications Bachelor’s or Master’s degree in Computer Science or related field AND 12+ years technical engineering experience, including leading architecture or large-scale systems initiatives. Hands-on experience with AI platform components, such as LLM orchestration, model hosting, vector storage, or retrieval-augmented generation (RAG) pipelines. Experience using and deploying machine learning models or integrating AI frameworks into large-scale systems. Strong understanding of performance tuning, security, and reliability at scale…
工作职责
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.
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.
• 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.