Principal Software Engineer

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

This Principal Software Engineer role focuses on optimizing the performance of Microsoft Edge, a user-facing product. The engineer will lead architectural evolution, drive data-informed improvements, modernize legacy code, and scale impact through performance tooling and AI-assisted diagnostics to ensure a fast, responsive, and reliable user experience.

What you'd actually do

  1. Own performance outcomes for Microsoft Edge user scenarios including site navigation, scrolling, input responsiveness, and startup.
  2. Lead architectural evolution to ensure browser performance remains durable as Edge scales and evolves.
  3. Drive data‑informed performance improvements using real‑world telemetry, traces, and experiments.
  4. Modernize legacy implementations and establish clear performance‑focused coding patterns and quality bars.
  5. Partner with feature teams to make performance a first‑class design constraint from concept to ship.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, Rust, C#, Java, JavaScript, or Python
  • equivalent experience

Nice to have

  • Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to C, C++, Rust, C#, Java, JavaScript, or Python
  • 3+ years experience designing and shipping performance-critical, large-scale software with measurable user impact (e.g., navigation, scrolling, input responsiveness, startup).
  • Proven ability to drive architectural changes and modernize complex/legacy codebases to improve performance, reliability, and maintainability.
  • Ability to scale impact through performance tooling/automation (including AI-assisted diagnostics/analysis) and to influence technical direction through reviews and cross-team collaboration.

What the JD emphasized

  • performance-critical
  • AI-assisted diagnostics