Principal Software Engineering

We are the Azure AI Inferencing infrastructure team that builds and runs the model-serving platform including, but not limited to, large OpenAI generative models. This team is at the forefront of delivering this innovation with massive scale powering every Azure OpenAI customer and scenario in the industry, both 3P and 1P customer like Bing and Office and solve exciting problems on the intersection of AI and Cloud.

We are looking for a Software Engineer, who is passionate about designing and building highly reliable, available platform to support model inferencing at the scale of billions of requests per day. You will be working on high throughput/low latency scenarios and drive performance optimization capabilities.

Microsoft is leading the AI strategy with an ambitious mission to democratize AI, make it an essential ingredient for delivering breakthrough customer experiences and to ensure the benefits of AI reach every person and organization on the planet, safely and responsibly. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Responsibilities :

- Lead architecture and design of complex, distributed systems; make key technical decisions and mentor engineers on design tradeoffs and best practices.

- Own solution quality end‑to‑end, including test strategy, security testing, reliability, and operational readiness.

- Drive cross‑team collaboration, identifying dependencies, resolving conflicts, and aligning delivery plans across partner teams.

- Act as DRI for live systems, leading incident response, root‑cause analysis, and prevention through automation and operational improvements.

- Champion security, privacy, compliance, and Responsible AI, establishing security invariants, auditability, and monitoring across the system.

- Lead automation and deployment excellence, enabling scalable, zero‑touch deployments with safe rollout and rollback strategies.

- Raise engineering standards, through code reviews, production-grade telemetry, performance/scalability improvements, and mentoring others

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent industry experience.