Microsoft

Senior Software Engineer

  • Redmond
  • On-site
  • Full-time

Posted

About the role

Lead architecture, design, and technical direction for the runtime infrastructure of Azure Managed Redis, one of Azure's fastest-growing data services. Design and build robust deployment, upgrade, and orchestration systems for distributed Redis clusters running across 70+ Azure regions worldwide. Drive the integration of Redis Enterprise software from Redis Inc. into Azure's managed environment, enabling seamless cluster upgrades while preserving high availability, data consistency, and performance under mission-critical workloads. Architect the end-to-end release platform across infrastructure, application, and observability layers to accelerate release velocity and improve deployment safety. Write high-quality, production-grade code in languages such as C# and Go while modeling best practices for reliability, testability, and operational excellence. Apply AI techniques (e.g., GitHub Copilot, LLMs, anomaly-detection models) to enhance DevOps, operations, and engineering workflows — detecting, diagnosing, and responding to issues across the global fleet. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, JavaScript, or Python OR equivalent experience. Master'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#, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, JavaScript, or Python OR equivalent experience. 2+ years of experience building and operating distributed, highly scalable online services on Kubernetes in Azure or a similar cloud platform. Experience using AI-assisted development tools, large language models, or automation technologies to improve software engineering workflows, developer productivity, testing, documentation, or operational efficiency. Demonstrated ability to improve engineering systems, developer productivity, service reliability, or product quality at scale.

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