Senior Software Engineer

Overview

Microsoft 365(M365) Intelligent Conversation and Communications Cloud is the platform that powers billions of real-time customer conversations across Microsoft’s first-party (Teams, Skype), second-party (Dynamics), and third-party solutions (through Azure Communication Services). The platform enables reliable and high-quality messaging, meeting, and audio/video calling services that work every time, from anywhere, seamlessly across all customer touchpoints. Conversations on our platforms are made more intelligent in real-time, empowering best-in-class productivity tools for the modern workplace where every call, meeting, or chat will make the next one better.

We are the team behind all the runtime policy scenarios across multiple products, and develop one of the largest scale, business-critical distributed systems in Microsoft. Our services protect organizations from data exposure or inappropriate/unwanted communication, and we process 25 billions of requests/day, enabling hundreds of millions of active enterprise as well as consumer users. The microservices are highly scalable, highly available, and extremely performant in geo-redundant, multi-tenant systems and honor data sovereignty, privacy, security, and compliance. We are seeking a Senior Software Engineer who will have an opportunity to work with a highly collaborative and fun team in a fast-learning environment.

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

• Build large-scale distributed services. Design, develop, and operate geo-distributed services on Kubernetes, Azure Cosmos DB, and Redis.

• Build data and ML infrastructure. Design and run large-scale data ingestion, real-time aggregation, and ML systems on Azure Data Lake, Azure ML, and Stream Analytics.

• Develop AI-first. Use AI tools with discipline across the whole development lifecycle, from requirements and design to code, tests, and operations. Own the quality of everything AI produces, and help the team raise its bar on AI-assisted engineering.

• Own architecture and design. Identify dependencies, lead design documents, and weigh trade-offs. Make sure systems meet requirements for scale, resiliency, performance, cost, disaster recovery, and compliance.

• Lead by example in code and code review. Write and mentor others to write extensible, maintainable, well-tested, secure code that's reused across products. Give timely, insightful reviews that make other engineers better.