Principal Software Engineer

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

Principal Software Engineer role focused on defining and leading the technical strategy for service-to-service authentication at Microsoft, with a significant emphasis on leveraging and building AI agents to automate workflows and improve engineering productivity. The role involves hands-on coding, architectural direction, and driving innovation in AI applications within a large-scale, security-critical platform.

What you'd actually do

  1. Define and own the long term technical strategy for service to service authentication, aligning that vision with organizational goals and communicating it effectively to senior leadership and other stakeholders
  2. Translate long term strategy into actionable shorter-term execution plans by driving technical and organizational consensus across multiple engineering teams, partner organizations, customers, and leadership, and ensuring successful delivery
  3. Provide technical leadership and mentorship across teams delivering security and resilience critical capabilities, setting architectural direction and raising the bar on quality through design leadership, code reviews, and direct hands-on technical engagement and coding
  4. Own and drive engineering fundamentals at the platform level, shaping investment priorities and proactively identifying and addressing systemic risks related to performance, scale, resilience, testability, and security across the organization
  5. Lead innovation in the application of AI by defining strategy and guiding adoption of AI driven tools to improve engineering productivity, while also shaping and delivering AI agents that automate operational and engineering workflows at scale

Skills

Required

  • Bachelor'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 OR equivalent experience
  • coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • security screening requirements

Nice to have

  • Master's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR 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 OR equivalent experience
  • 6+ years of experience designing and implementing features of high-scale distributed cloud services
  • 3+ years of experience as a technical lead, driving strategic decisions and delivering high-impact technical results
  • 3+ years of technical leadership in defining and building developer experiences and scalable systems, preferably in the Generative AI, Machine Learning domain
  • 2+ years of hands-on experience designing SDKs or client-side frameworks, with a deep interest in performance engineering, latency reduction, and efficient resource utilization
  • Experience leading cross-functional engineering efforts across distributed teams
  • Experience delivering customer-facing software products or platform capabilities in production environments
  • Demonstrated proficiency around leveraging AI to build AI systems and a passion to make this technology accessible to everyone
  • Proven record of identifying challenges, making clear judgment calls on tradeoffs, and making systemic changes for lasting impact, while bringing value to customer quickly
  • Clarity in communication and ability to influence without authority when stakes are high

What the JD emphasized

  • AI agents that automate operational and engineering workflows at scale
  • Define and own the long term technical strategy for service to service authentication
  • Lead innovation in the application of AI by defining strategy and guiding adoption of AI driven tools to improve engineering productivity

Other signals

  • AI agents that automate operational and engineering workflows at scale
  • Define and own the long term technical strategy for service to service authentication
  • Lead innovation in the application of AI by defining strategy and guiding adoption of AI driven tools to improve engineering productivity