Senior Software Engineer - Coreai

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

Senior Software Engineer role focused on building and operating scalable distributed systems for Azure Dev Services. The role involves integrating AI-assisted development tools and AI-enhanced features using LLMs and RAG, contributing to the development of AI-powered solutions in production environments.

What you'd actually do

  1. Own and operate highly scalable, reliable, and low-latency distributed systems that power mission-critical workloads
  2. Design and implement features that enable configuration management, monitoring, analytics, and observability for modern cloud applications
  3. Drive integration with other Azure services to deliver seamless customer experiences
  4. Write high-quality, well-tested code and own the DevOps lifecycle, including monitoring, alerting, and incident response
  5. Integrate AI-assisted development tools to improve engineering productivity and code quality

Skills

Required

  • 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#, Java, JavaScript, or Python OR equivalent experience
  • 4+ years of experience with cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
  • 1+ years of proficiency with AI-assisted development tools (e.g., GitHub Copilot, IntelliCode)

Nice to have

  • 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#, Java, 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#, Java, JavaScript, or Python OR equivalent experience.
  • Experience with .NET is a plus
  • Experience developing, deploying, or integrating AI-powered solutions in production environments
  • Experience building or integrating AI applications using technologies such as LLMs, Model Context Protocol (MCP) servers, or RAG pipelines
  • Working knowledge of web and cloud technologies, including containers, microservices, and CI/CD pipelines
  • Familiarity with distributed systems, cloud-native architectures, or managed cloud services

What the JD emphasized

  • AI-assisted development tools
  • AI-enhanced features using technologies such as Large Language Models (LLMs), Model Context Protocol (MCP) servers, and Retrieval-Augmented Generation (RAG)
  • developing, deploying, or integrating AI-powered solutions in production environments
  • building or integrating AI applications using technologies such as LLMs, Model Context Protocol (MCP) servers, or RAG pipelines

Other signals

  • integrates AI-assisted development tools
  • integrates AI-enhanced features using LLMs, MCP servers, and RAG
  • develops, deploys, or integrates AI-powered solutions in production environments