Principal Software Engineer

Microsoft Microsoft · Big Tech · United States · Software Engineering

This Principal Software Engineer role focuses on building and managing a hyperscale deployment system, leveraging AI to enhance efficiency, reliability, and automation. The role involves leading a team, mentoring engineers on AI-powered development practices, and driving innovation through AI solutions for deployment intelligence and operational excellence. It requires experience with AI-native development, LLMs, and integrating AI into the software development lifecycle.

What you'd actually do

  1. Work with engineers, product managers, and partner teams to deliver experiences with the right overall design and architecture, leveraging AI where it can meaningfully improve deployment efficiency, reliability, and customer outcomes.
  2. Provide mentorship and coaching to engineers both in, and beyond, your team, including the adoption of modern AI-powered development practices and tools.
  3. Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing.
  4. Drive innovation through automation and AI-powered solutions to improve deployment intelligence, operational efficiency, and service reliability at hyperscale.
  5. Ensure your team delivers clean, well-thought-out code with an emphasis on quality, performance, simplicity, durability, scalability, maintainability, and effective use of AI-assisted engineering practices.

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++, C#, Java, JavaScript, or Python
  • coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

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++, C#, Java, JavaScript, or Python
  • Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Proficiency in AI-native development — working within Agent Harnesses (GitHub Copilot CLI, Coding Agents), authoring Markdown specs/ADRs and YAML configs as Agent-consumable inputs, orchestrating multi-step Agentic workflows across the SDLC, and reviewing Agent-generated code and PRs with production-grade rigor.
  • Fundamentals in data structures, algorithms, object-oriented design, and scalable systems.
  • Experience building, testing, debugging, and maintaining production-quality software, following established engineering practices as well as leveraging large language models (LLMs).
  • Problem-solving and technical judgment skills, with the ability to design scoped solutions, debug complex issues, and improve service performance.
  • Experience with cloud platforms and distributed/service-oriented architecture.
  • Experience with reliability, monitoring, and performance optimization practices.
  • Experience in driving AI (LLM/ML) based engineering solution.

What the JD emphasized

  • AI-native development
  • orchestrating multi-step Agentic workflows
  • leveraging large language models (LLMs)
  • AI (LLM/ML) based engineering solution

Other signals

  • AI-driven innovation to improve deployment reliability, automation, and operational excellence
  • leverages AI where it can meaningfully improve deployment efficiency, reliability, and customer outcomes
  • Drive innovation through automation and AI-powered solutions to improve deployment intelligence, operational efficiency, and service reliability at hyperscale
  • emphasis on quality, performance, simplicity, durability, scalability, maintainability, and effective use of AI-assisted engineering practices
  • Proficiency in AI-native development — working within Agent Harnesses (GitHub Copilot CLI, Coding Agents), authoring Markdown specs/ADRs and YAML configs as Agent-consumable inputs, orchestrating multi-step Agentic workflows across the SDLC, and reviewing Agent-generated code and PRs with production-grade rigor.
  • leveraging large language models (LLMs)
  • driving AI (LLM/ML) based engineering solution