Principal Software Engineering Manager

Microsoft Microsoft · Big Tech · Prague, Prague, Czech Republic · Software Engineering

Engineering Manager for M365 Copilot Evaluation Platform, focusing on AI quality, safety, and impact. The role involves managing a team, setting technical direction, and ensuring high-scale cloud services for AI evaluation, with a strong emphasis on AI-native development practices.

What you'd actually do

  1. Manage, coach, and support a team of individual contributors on the Copilot Shadow Experimentation platform
  2. Grow the team by developing engineers into independent senior and principal contributors.
  3. Create clarity for the team by setting the right priorities and engineering direction for evolving the platform.
  4. Apply high-scale design principles across every tier of the service, ensuring agility and reliability.
  5. Quickly diagnose and drive resolution of problems across a complex, distributed service ensuring high reliability.

Skills

Required

  • Experience leading and developing engineering teams
  • Experience designing, developing, and maintaining large-scale software systems
  • Experience incorporating AI-assisted or AI-native development practices into the software development lifecycle
  • Proficiency in one or more programming languages such as C, C++, C#, Java, JavaScript, or Python

Nice to have

  • Advanced degree in Computer Science, Engineering, or a related technical field
  • Experience in backend, distributed systems, platform, infrastructure, or developer productivity engineering
  • Experience building scalable, reliable, and maintainable services and platforms
  • Experience using data and operational metrics to inform engineering decisions
  • Ability to work effectively in a fast-paced and evolving environment
  • Demonstrated ownership and accountability in delivering results

What the JD emphasized

  • AI impacts millions of users
  • evaluation system to the next level
  • understand what “Good AI” means
  • quality, reliability, and user trust are treated as first‑class engineering concerns
  • Proficiency with AI and agentic technologies is a must
  • evaluating AI quality, safety, and impact across Copilot experiences used by millions of users
  • AI-Native Development
  • disciplined use of, and improving artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC)
  • experimenting with AI tools and practices to improve efficiency and productivity
  • AI-assisted or AI-native development practices into the software development lifecycle

Other signals

  • evaluating AI quality, safety, and impact
  • Copilot Shadow Experimentation platform
  • AI-Native Development