微软Senior Software Engineer
任职要求
Required Qualifications: • 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 OR equivalent experience. • Solid computer science fundamentals and background knowledge in AI; • Prior experience in AI-related roles is preferred; • Proficient in programming languages and frameworks such as Python, C#, Java, and frontend development tools; • Strong communication skills and a collaborative mindset. Preferred / Additional Qualifications: • 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 OR equivalent experience. 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
• Lead code reviews to ensure adherence to engineering standards, test coverage, and secure coding practices. Provide feedback and mentorship to peers, and apply tools and patterns that enhance reliability, diagnosability, and maintainability. • Develop scalable and secure design proposals, collaborating across teams to resolve dependencies and validate design hypotheses. Ensure solutions meet performance, compliance, and cost expectations. • Create and maintain test plans that validate functionality and security. Leverage automation and AI tools to improve test reliability and coverage, and ensure testability is embedded in design. • Apply secure design principles and engineering best practices to build resilient systems. Drive automation in deployment, ensure compliance with global regulations, and integrate security monitoring and incident response mechanisms. • Translate product requirements into actionable plans, estimate effort, and guide execution. Ensure safe deployment practices, flighting strategies, and rollback plans are in place to support efficient and secure releases. • Integrate telemetry and observability into systems to monitor performance and security. Act as a Designated Responsible Individual (DRI), lead incident response efforts, and continuously improve live site operations and support documentation. • Collaborate with stakeholders to understand user needs and incorporate feedback into product design. Ensure privacy and security requirements are met, and establish feedback loops to measure impact and value.
As a pivotal member of the Copilot Team, you will bring unique perspectives and expertise to the organization, driving innovative features and delivering transformative AI-powered experiences:• This is an IC role, Coding / engineering design time >70%• Manage complex projects from conception to implementation, with a focus on delivering AI-driven user interfaces and performance-optimized web applications.• Coordinate technical delivery through sprints, fostering collaboration throughout the project lifecycle.• Collaborate across geographies and time zones to establish best practices and develop automated processes that mitigate development risks.• Investigate and debug complex performance issues in applications, ensuring optimal user experience and system efficiency.• Design and implement performance testing strategies to proactively address bottlenecks.• Work closely with Product Designers, Product Managers, and Engineers to deliver AI-enhanced products that delight users.• Drive team-wide investments in infrastructure and foundational systems to support long-term technical roadmaps.• Solve technical challenges to deliver outstanding outcomes for customers and the business.
• Build, maintain, and enhance data ETL pipelines for processing large-scale data with low latency and high throughput to support Copilot operations.• Own data quality initiatives including monitoring, validation, and remediation to ensure integrity across attribution datasets and downstream dashboards.• Implement schema management solutions that enable quick and seamless evolution of attribution data without disrupting consumers.• Develop and maintain infrastructure that supports both batch and real-time attribution requirements.• Collaborate with product managers, marketing analysts, and data scientists to deliver insights for campaign optimization and growth strategies.• Design scalable attribution data architectures that can handle growing data volumes and evolving business needs.• Implement comprehensive monitoring and observability solutions for attribution pipelines, including SLA tracking and automated alerting.
• Design, develop, and manage Streaming and Batch pipelines, supporting key functionalities such as large-scale index construction, web page crawling and feature extraction, image processing, and context re-writing. • Optimize continuously a platform to manage, schedule, and monitor hundreds of pipelines. • Optimize continuously a platform to view, track, debug, and operate massive scale Ads Data. • Evaluate and optimize code and design, to maximize performance, minimize complexity. • Mentor junior SDE and solely drive feature development from ground zero.
Build/Improve experiment platforms for new scenarios.Build data pipelines on multiple computation platforms for reporting, analysis and metrics pre-computation with stable SLA and good quality.Build agents for productivity improvement.