Senior Software Engineer

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN · Software Engineering

Senior Software Engineer role in Microsoft's CoreAI division, focusing on building AI-powered developer tools and planet-scale platforms with enterprise trust, security, and reliability. The role involves designing, building, and operating core platform services for developers across the entire application lifecycle, including AI-native engineering practices and AI-enabled systems to improve various aspects of the software development lifecycle.

What you'd actually do

  1. AI-powered cloud services and platforms that support developer and enterprise workflows, owning them end-to-end—from architecture, design and implementation to deployment and live-site operations.
  2. 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.
  3. AI-enabled engineering and lifecycle systems that improve testing efficiency, quality analysis, incident triage, and developer productivity across the software development lifecycle.

Skills

Required

  • 7-12 years of experience building production software
  • C#
  • C++
  • Go
  • Java
  • Python
  • Strong understanding of software engineering fundamentals
  • data structures
  • problem-solving

Nice to have

  • Experience working in Linux environments
  • open-source projects
  • containers
  • orchestration technologies such as Docker and Kubernetes
  • cloud infrastructure (Azure, AWS, or equivalent)
  • site reliability engineering (SRE) practices
  • AI-assisted development
  • data-driven engineering workflows
  • Azure resource providers
  • platform extensibility
  • security
  • compliance
  • responsible AI concepts

What the JD emphasized

  • enterprise trust
  • security
  • reliability
  • AI as a core building block
  • AI-native engineering
  • responsible AI practices

Other signals

  • AI-powered developer tools
  • planet-scale platforms
  • enterprise trust, security, and reliability
  • AI as a core building block
  • AI-enabled engineering and lifecycle systems
  • AI embedded across design, coding, testing, release validation, and live-site operations