Software Engineer II, Azure Intelligent Container Platform - CoreAI

Microsoft•Redmond, WA

About The Position

Join Microsoft's Azure Intelligent Container Platform team within CoreAI to build infrastructure behind next-generation AI-powered cloud services. Azure AI Services help customers build intelligent applications using deep learning and large language models. The team turns emerging AI technologies into production-ready Azure services that deliver reliability, scale, simplicity, and performance. The role involves working with technology providers and engineering teams to bring AI technologies to Azure, from architecture and productization through platform engineering, deployment, performance, reliability, security, and customer experience. You will build highly available distributed systems across global public and private datacenters, engineer resilient cloud-native platforms, and own solutions through design, implementation, testing, deployment, monitoring, and continuous improvement. The work addresses distributed systems, performance, availability, scalability, security, privacy, and user experience, supporting AI services used by customers around the world.

Requirements

Bachelor's degree in Computer Science or a related technical field and 2+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years.

Nice To Haves

Proficiency with modern AI technologies and tools, including hands-on use of LLMs, Generative AI, AI coding assistants or agents, and AI/ML frameworks in day-to-day engineering.
Strong analytical and problem-solving skills, a quality mindset, and a commitment to designing robust, maintainable, production-grade software.
Strong hands-on programming experience in one or more of C#, Python, or Go.
Experience with Web APIs, performance/load testing, security, and privacy, and understanding of building reliable production services.
Strong communication and collaboration skills, with the ability to work in a fast-paced, global engineering environment and drive projects from concept to production.
Experience building, developing, or operating cloud platforms, particularly Microsoft Azure.
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.

Responsibilities

Design and develop highly available, scalable distributed systems running across global public and private datacenters.
Build fault-tolerant, self-managing, self-healing platforms designed for operational excellence.
Use Docker, Kubernetes, open-source technologies, and cloud platforms to address infrastructure challenges.
Turn evolving AI and cognitive technologies into reliable, secure, performant, easy-to-use Azure services.
Drive solutions from architecture and system design through implementation, testing, deployment, monitoring, and continuous improvement.
Address challenges in distributed systems, performance, availability, scalability, security, privacy, and user experience.
Build products and platforms that enable AI experiences for customers around the world.
Collaborate with technology providers and engineering teams to bring AI technologies to Azure across architecture, productization, platform engineering, deployment, and customer experience.