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. Ability to analyze and resolve complex system issues across infrastructure and application layers. Demonstrated ability to lead technical reviews, influence product direction, and make key decisions based on data and long-term impact. Excellent communication skills, capable of explaining complex systems and architectural decisions to both technical and non-technical stakeholders. Passion for building high-quality platforms and mentoring others to raise the technical bar. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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.
Architect and implement core infrastructure components, drive technical direction, mentor engineers, and ensure high standards for scalability, security, and performance.
• Act as the craft owner for LLM engineering at Supercell — setting direction, sharing best practices, and raising the bar for what “great” looks like in LLM-powered systems. • Drive adoption of a wide range of LLM and agentic applications (e.g. in-game bots, player support, social insights, internal productivity tools). • Champion AI development tools as a particularly high-leverage use case — helping our teams accelerate workflows, code smarter, and build better systems faster. • Partner closely with game and functional teams to evangelize LLM capabilities and turn vague opportunities into concrete solutions. • Serve as a bridge between technical and non-technical stakeholders, clearly communicating the strengths, limitations, and business value of different approaches. • Monitor emerging developments in the LLM and agents space; assess technologies for safety, reliability, and performance; and build our internal “stack” of recommended approaches. • Lead the design and implementation of robust evaluation, monitoring, and safety frameworks for production LLM-powered systems. • Rapidly prototype and deliver production-grade systems — but also coach, mentor, and enable other engineers to build confidently themselves.