4 days ago
Suzhou, China or Shanghai, ChinaSenior
Responsibilities
- Design, develop, and operate large-scale distributed storage and high-availability systems covering replication, database copy management, failover, recovery, and storage architecture.
- Build and apply AI agents and agentic workflows to automate incident investigation, mitigation, root-cause analysis, software development, testing, debugging, and operational processes.
- Apply machine learning, data science, predictive models, and decision models to operational data to identify risks and optimize reliability and resource efficiency.
- Drive complex engineering projects independently from technical design through implementation, testing, deployment, production operations, and continuous improvement.
- Collaborate with storage, infrastructure, and AI engineering teams to solve complex technical problems and advance system architecture.
- Evaluate and adopt emerging technologies and engineering approaches.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Preferred qualifications include a master's degree and 6+ years of technical engineering experience, or a bachelor's degree and 8+ years of experience, or equivalent experience.
- Experience designing, developing, and operating large-scale distributed systems, cloud infrastructure, or backend services.
- Understanding of software engineering fundamentals, system architecture, concurrency, reliability, and fault tolerance.
- Hands-on experience using AI and developing or integrating AI agents and agentic workflows for practical engineering problems.
- Foundational knowledge of machine learning, statistical analysis, or data-driven modeling.
- Experience with distributed storage systems, databases, replication protocols, consistency models, erasure coding, or Shingled Magnetic Recording.
- Experience building production AI agent systems with tool integration, Model Context Protocol, orchestration, evaluation, safety guardrails, and autonomous task execution.
- Experience with applied machine learning, data science, predictive modeling, anomaly detection, or decision optimization using large-scale operational telemetry.
- Experience automating software development, testing, troubleshooting, or incident management through agentic engineering.
- Experience designing, troubleshooting, and optimizing highly available services in large-scale cloud production environments.
Tech Stack
Categories
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.