Software Engineer

Microsoft is hiring for the role of Software Engineer!

Responsibilities

• AI-powered cloud services and platforms that support developer and enterprise workflows, owning them end-to-end—from architecture and implementation to deployment and live-site operations.
• Cloud-to-edge platform capabilities, including Azure resource providers, data-plane integrations, and portal experiences that enable secure, scalable management of modern applications and AI workloads.
• AI-enabled engineering and lifecycle systems that improve testing efficiency, quality analysis, incident triage, and developer productivity across the software development lifecycle.
• Outcome-driven, platform-first approach: build durable platforms guided by metrics, telemetry, and customer feedback, with clear ownership across the full DevOps lifecycle.
• AI-native engineering: design, build, and operate systems with AI embedded across design, coding, testing, release validation, and live-site operations, while maintaining correctness, safety, and trust.
• Enterprise-grade trust: security, privacy, compliance, reliability, and responsible AI practices are treated as first-class engineering concerns.
• Continuous growth and collaboration: deepen skills in distributed systems, cloud platforms, and applied AI through hands-on production work in an inclusive, supportive environment.

Requirements

• Bachelor’s or Master’s degree in Computer Science, or equivalent practical experience.
• 1-3 years of experience building production software using one or more modern programming languages such as C#, C++, Go, Java or Python.
• Strong understanding of software engineering fundamentals, data structures, and problem-solving.
• Ability to learn new technologies quickly and adapt to deliver customer and business impact.
• Experience working in Linux environments and with open-source projects.
• Familiarity with containers and orchestration technologies such as Docker and Kubernetes.
• Experience with cloud infrastructure (Azure, AWS, or equivalent).
• Exposure to site reliability engineering (SRE) practices.
• Exposure to AI-assisted development and data-driven engineering workflows.
• Knowledge of Azure resource providers, platform extensibility, and security, compliance, or responsible AI concepts.