The Microsoft AI Frameworks team develops the software, performance systems, and engineering tools that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. We work across model architectures, frameworks, compilers, runtimes, libraries, observability, benchmarking, and hardware platforms—including NVIDIA and AMD GPUs and Microsoft silicon. Our engineers, partner with model developers, researchers, hardware teams, and production services to accelerate model onboarding, improve performance and reliability, reduce deployment time and hardware footprint, and turn performance insights into durable platform capabilities.

This is a hands-on technical leadership role for an engineer who can establish direction and lead teams through ambiguous, end-to-end systems challenges. Successful candidates combine strong software engineering fundamentals with deep curiosity about AI workloads, use disciplined measurement to guide decisions, and create alignment across organizational boundaries to deliver measurable production impact.

As a Principal Software Engineer - AI Frameworks, you will serve as a technical lead for high-impact initiatives spanning AI frameworks, performance engineering, benchmarking, and tooling. You will establish technical direction, make consequential architectural decisions, and lead engineers across teams through the design and delivery of solutions that improve model velocity, platform efficiency, and production reliability. You will also identify systemic opportunities, align stakeholders around durable architectures and success measures, and remain hands-on in critical areas of implementation.

At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.

• Own the technical vision, architecture, roadmap, and multi-release execution strategy for critical AI framework, performance, benchmarking, or developer-productivity capabilities.

• Lead technical alignment across teams by shaping architecture and priorities, resolving competing requirements, and holding researchers, product groups, infrastructure owners, and hardware partners accountable to clear decisions, execution plans, and measurable outcomes.

• Build technical leadership capacity across the organization by mentoring engineers, developing emerging technical leads, establishing high standards for quality and maintainability, and creating an inclusive engineering culture in which teams can execute effectively at scale.

• Steer ambiguous, cross-stack investigations and investments spanning models, frameworks, compilers, runtimes, systems, services, and silicon; set technical priorities, resolve trade-offs, and drive teams to decisions.

• Provide hands-on technical leadership by setting the engineering approach, delegating and unblocking critical work, and directly contributing through prototypes, critical-path implementation, design and code reviews, complex debugging, and operational readiness.

• Spearhead common measurement, automation, observability, and engineering mechanisms that turn one-off analyses into scalable platform capabilities.

• Drive measurable improvements in model onboarding velocity, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.

• Embody Microsoft’s culture and values.