Principal Software Engineer Manager- Ctj- Poly

Microsoft Microsoft · Big Tech · Reston, VA +3 · Software Engineering

Principal Software Engineer Manager to lead engineering teams responsible for developing, deploying, operating, and continuously improving Azure services within Microsoft Specialized Clouds. This role focuses on AI-native development, guiding teams on the use of AI tools and Responsible AI practices throughout the SDLC, ensuring operational rigor, automation, and compliance in regulated cloud environments.

What you'd actually do

  1. Leads team on the disciplined use of, and improving artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC).
  2. Guides team on proactively taking responsibility for the content of their AI-generated requirements, design documents, code, and other assets, and assisting other members of the team to do the same.
  3. Leads team on incorporating Responsible AI practices into the SDLC to ensure appropriate controls over AI-generated assets.
  4. Coaches team on applying SDLC and engineering health measures (e.g., Accelerate, SPACE framework, Engineering System Success Playbook [ESSP]) to guide improvements to processes and practices, especially those involving AI.
  5. Leads team on experimenting with AI tools and practices to improve their own capabilities, and providing recommendations on how to adopt them to others.

Skills

Required

  • Software engineering management
  • Cloud platform engineering
  • Live site operations
  • Regulated cloud delivery
  • AI tools and practices
  • Responsible AI
  • SDLC improvement
  • Incident response
  • Change management
  • Compliance
  • Automation
  • Code review
  • Test strategy
  • Scalability
  • Reliability

Nice to have

  • Azure services
  • Accelerate framework
  • SPACE framework
  • ESSP

What the JD emphasized

  • regulated cloud delivery
  • unique regulatory constraints
  • compliance workflows
  • Responsible AI practices

Other signals

  • leading engineering teams
  • developing, deploying, operating, and continuously improving Azure services
  • AI tools and practices across the software development lifecycle (SDLC)
  • Responsible AI practices
  • operational rigor
  • reduce manual production touches through automation
  • incident response, change management, and compliance workflows