Principal Software Engineer, Integration and Automation - AI Infrastructure

Microsoft is seeking a Principal Software Engineer on the Integration and Automation team. The role focuses on building and operating AI-powered automation, continuous integration and continuous delivery systems, validation services, distributed services, and developer platforms to improve build, test, deployment, and production workflows at scale.

Responsibilities:

• Own significant systems from design through production operation. Work across artificial intelligence automation, continuous integration and continuous delivery, distributed services, developer tooling, reliability, and code intelligence while contributing to architecture, engineering practices, and technical decisions within the team’s domain
• Own a core capability end to end. Lead architecture, design documentation, implementation, quality, and operational health for services or technologies within a defined platform area, including artificial intelligence workflow automation, continuous integration and continuous delivery orchestration, build and validation services, developer experiences, code intelligence, or production operations. Lead technical reviews, contribute to roadmap decisions, and communicate trade-offs involving cost, latency, reliability, and quality
• Improve engineering workflow quality with evidence. Build evaluation and validation systems for artificial intelligence-assisted changes, builds, tests, deployments, and code-intelligence experiences. Use measurable results to improve automation accuracy, release confidence, developer efficiency, and platform reliability
• Scale automation and delivery platforms. Design systems that support large repositories, high-volume builds, parallel validation, dependable deployments, branch-aware workflows, resilient external integrations, rate-limit management, and effective cost controls
• Operate a reliable production service. Define service-level objectives, alerts, runbooks, and incident practices. Strengthen multitenant authentication, secrets management, and network policy, and participate in on-call ownership for the systems you build
• Integrate with engineering workflows. Expose automation, validation, delivery, and code-intelligence capabilities through Model Context Protocol (MCP) and application programming interfaces (APIs), connect to existing developer and continuous integration and continuous delivery systems, and translate partner feedback into practical platform improvements
• Raise engineering standards and help the team deliver high-value work. Provide substantive code and design reviews, mentor engineers, model strong practices in testing, observability, migrations, and release discipline, identify technical gaps, develop proposals, build alignment with partner teams, and drive agreed solutions through delivery

Requirements:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
• 5+ years of experience building, testing, launching, and operating backend services or data-intensive systems in production
• Experience owning the design and architecture of a significant system, including writing design documents and leading technical reviews
• Experience in one or more of the following areas: distributed systems and concurrency; continuous integration and continuous delivery platforms; workflow orchestration or developer automation; large-scale data pipelines; cloud-native containerized services on Kubernetes; or search, retrieval, and code intelligence
• Demonstrated ability to define an ambiguous problem and drive it through implementation, launch, and measurable results
• Master's degree or PhD in Computer Science or a related technical field
• 5+ years of experience delivering production software in one or more of the following areas: artificial intelligence-enabled automation, agentic workflows, automated software engineering tasks, evaluation frameworks, retrieval-augmented generation, embedding pipelines, or the Model Context Protocol (MCP)
• Experience operating vector, graph, or relational databases at scale, such as Qdrant, FAISS, Neo4j, or PostgreSQL
• Experience building or operating continuous integration and continuous delivery systems, build and test infrastructure, release automation, deployment orchestration, policy gates, developer self-service platforms, or cloud services using infrastructure as code and Kubernetes deployment tooling
• Experience with Google Remote Procedure Call (gRPC) service design, FastAPI or similar frameworks, and TypeScript and React front ends
• Experience building developer tools, engineering automation, continuous integration and continuous delivery platforms, build or test systems, static analysis, code search, or code-intelligence products
• Experience leading a technical workstream, mentoring engineers, or serving as the recognized owner of a system used by other teams