Overview
Build the platform that makes every engineering team more effective!
We are looking for a Principal Software Engineer who combines deep distributed systems expertise with an AI-forward perspective to shape the next generation of our platform. Our ambition is to make building and operating software fundamentally simpler: turn complex infrastructure into intuitive capabilities, make reliability and security part of the default experience, and use AI to eliminate work that slows engineers down.
This is an opportunity to create impact beyond any single service or feature. The abstractions you design, the systems you build, and the engineering practices you establish will help teams deliver better products with greater speed and confidence. You will tackle challenging problems across scalability, performance, observability, and developer experience—while rethinking how intelligent automation can change the way a platform is built and operated.
As a hands-on technical leader, you will shape architectural direction, write production code, lead cross-team initiatives, and take ideas from early exploration through production adoption. We are looking for someone who questions established approaches, sees opportunities where others see operational overhead, and pairs ambitious thinking with the engineering discipline to deliver dependable systems. If you want to build technology that amplifies the work of others—and help define what platform engineering looks like in an AI-enabled world, this role offers that opportunity.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Set technical direction. Define and drive a platform roadmap that connects long-term architectural investments with the most important needs of engineering teams and the business.
• Apply AI to meaningful engineering problems. Develop AI-assisted and agent-based capabilities for workflows such as troubleshooting, testing, migrations, and operational analysis. Establish evaluations and safeguards that make their results trustworthy.
• Treat the platform as a product. Work directly with partner teams to understand friction, validate solutions, and turn repeated challenges into self-service capabilities that engineers choose to adopt.
• Make safe delivery easier. Build automated validation, progressive rollout, observability, and recovery mechanisms that help teams move quickly without transferring unnecessary risk to production.
• Own outcomes end to end. Lead initiatives from problem definition and architecture through implementation, adoption, and ongoing operation. Measure success through developer experience, reliability, pe
