This role offers end-to-end ownership and real-world impact. You will work closely with leading technology providers and engineering teams to bring cutting-edge AI technologies to Azure—from architecture and productization to platform engineering, deployment, performance, reliability, security, and customer experience. You will solve challenging problems across the entire software stack and have the opportunity to influence both how the technology is built and how millions of customers experience AI at Azure scale. You will: Build for massive scale: Design and develop highly available, scalable distributed systems running across global public and private datacenters. Engineer for resilience: Build platforms that are fault-tolerant, self-managing, self-healing, and designed for operational excellence. Push cloud-native innovation: Leverage Docker, Kubernetes, open-source technologies, and cloud platforms to solve complex infrastructure challenges. Make AI production-ready: Turn rapidly evolving AI and cognitive technologies into reliable, secure, performant, and easy-to-use Azure services. Own the full lifecycle: Drive solutions from architecture and system design through implementation, testing, deployment, monitoring, and continuous improvement. Solve hard problems: Tackle challenges in distributed systems, performance, availability, scalability, security, privacy, and user experience. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: AI-native mindset: Proficient in modern AI technologies and tools, with hands-on experience using LLMs, Generative AI, AI coding assistants/agents, and AI/ML frameworks in day-to-day engineering. You actively explore new AI capabilities and use AI to accelerate development, automate workflows, solve complex problems, and build smarter products. Strong engineering fundamentals: Excellent analytical and problem-solving skills, a strong quality mindset, and a passion for designing and building robust, maintainable, production-grade software. Programming: Strong hands-on programming experience in one or more of C#, Python, or Go. Production engineering: Experience with Web APIs, performance/load testing, security, and privacy, with an understanding of building reliable services for production environments. Ownership & collaboration: Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, global engineering environment and drive projects from concept to production. Hands-on experience with Docker, Kubernetes, and containerized applications. Experience with large-scale distributed systems, cloud-native architecture, AI/ML infrastructure, or platform engineering. Experience working with or contributing to open-source technologies and communities. Experience building highly available, fault-tolerant, self-managing, or self-healing systems. Experience with Big Data, AI infrastructure, or large-scale data/compute platforms. Proficiency in Chinese to support collaboration with global engineering teams on Azure AI and cloud platform technologies.