Job description

Overview Are you a software engineer who loves code, moves fast, and enjoys solving problems at scale? Are you excited about AI and want to build the platform that makes AI reliable, resilient, and effortless to operate at global scale? Do you want to work with cutting-edge open-source and cloud technologies and build systems that are fault-tolerant, self-managing, self-healing, and highly scalable across public and private datacenters around the world? Do AI, Big Data, cloud infrastructure, Docker, Kubernetes, and distributed systems excite you? If yes, come build with us. Join the Azure Intelligent Container Platform team within CoreAI and help shape the infrastructure behind the next generation of AI-powered cloud services. Azure AI Services enable customers to build intelligent applications with powerful capabilities to see, hear, speak, understand, and interpret using deep learning and large language models (LLMs). Our mission is to transform these breakthrough AI technologies into production-ready, first-class Azure services —delivering the reliability, scale, simplicity, and performance customers need to bring AI innovations to life. Responsibilities 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. Ship technology that matters: Build products and platforms that enable AI experiences for customers around the world. Qualifications Required Qualifications • 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. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years. Preferred Qualifications • 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. • 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. #CoreAI Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

If yes, come build with us.
Join the Azure Intelligent Container Platform team within CoreAI and help shape the infrastructure behind the next generation of AI-powered cloud services.
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 .
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.
Ship technology that matters: Build products and platforms that enable AI experiences for customers around the world.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years.

Nice-to-haves

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.
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.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aidockerkubernetesazurejavajavascriptpythonmlgo

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