New 
Senior Software Engineer
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 22, 2025 | |
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OverviewCore AI at Microsoft powers intelligent experiences across Microsoft 365, Azure, and beyond. The Dotnet Engineering team builds and operates the engineering system that powers .NET, one of the most widely used open-source developer platforms. Our infrastructure enables the building, testing, and deployment of .NET across multiple environments, ensuring reliability, scalability, and performance for millions of developers worldwide. What We DoEngineering System Development: Design and maintain pipelines, tooling, and automation that build, validate, and release .NET.AI-Driven Optimization: Apply machine learning and AI techniques to improve build efficiency, reduce cycle times, and predict failures before they occur.Cloud-Scale Infrastructure: Operate services that run at global scale, leveraging Azure for distributed builds and testing.Security & Compliance: Ensure secure, compliant workflows for all .NET releases.Developer Productivity: Innovate on developer experiences by integrating intelligent automation and telemetry-driven insights. We are seeking engineers passionate about .NET and AI-driven engineering systems. This role focuses on designing and implementing features for the engineering system that builds, tests, and deploys .NET, leveraging AI to optimize workflows, accelerate development, and enable next-generation developer experiences. 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.
ResponsibilitiesEngineering System Feature Development Design and implement new features for the .NET engineering system that automates build, test, and deployment processes. Enhance reliability and scalability of pipelines for .NET workloads across distributed environments. AI-Driven OptimizationIntegrate AI capabilities into build and test workflows (e.g., reduction of engineering toil, intelligent test selection, failure analysis). Collaborate with ML teams to embed LLMs and generative AI into developer tools for automated code insights and diagnostics. Distributed Systems & InfrastructureDevelop cloud-native services using .NET Core and Azure to support AI orchestration and system scalability. Implement CI/CD automation enriched with AI-driven insights for performance and efficiency. Cross-Functional CollaborationPartner with product engineering and PM teams to align .NET engineering systems with AI innovation goals. Define metrics and telemetry for AI-enhanced build and deployment processes. Security & ComplianceApply Responsible AI principles, privacy safeguards, and compliance checks within .NET engineering workflows. | |