Software Engineer II
Microsoft
Software Engineer II
Redmond, Washington, United States
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Overview
Are you passionate about building high-performance, low-latency systems that power mission-critical workloads? The Azure Dev Services team delivers a suite of fully managed Azure services including Azure App Configuration, Azure Managed Grafana, Azure Managed Redis, and Azure Diagnostics that help developers build, monitor, and scale modern cloud applications with confidence.
As a Software Engineer II on the Azure Dev Services team, you’ll take ownership of key product areas, collaborate across Azure, and help shape the future of developer infrastructure and observability. This opportunity will allow you to deepen your distributed systems expertise, work with cutting-edge AI technologies, and grow your impact across Azure.
This role is part of a dynamic and collaborative team in the Developer Division under the CoreAI business group.
Microsoft offers a hybrid work environment and is remote-friendly.
Microsoft Culture
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.
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.
- OR equivalent experience.
- 1+ years of proficiency with AI-assisted development tools (e.g., GitHub Copilot, IntelliCode).
- Experience with cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications
- Master's Degree in Computer Science or related technical field AND 2+ 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 4+ 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.
Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
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Responsibilities
Responsibilities
- Own and operate highly scalable, reliable, and low-latency distributed systems that power mission-critical workloads.
- Design and implement features that enable configuration management, monitoring, analytics, and observability for modern cloud applications.
- Drive integration with other Azure services to deliver seamless customer experiences.
- Write high-quality, well-tested code and own the DevOps lifecycle, including monitoring, alerting, and incident response.
- Integrate AI-assisted development tools to improve engineering productivity and code quality.
- Contribute to AI-enhanced features using technologies such as Large Language Models (LLMs), Model Context Protocol (MCP) servers, and Retrieval-Augmented Generation (RAG).
- Mentor others and share knowledge to improve team capabilities and engineering practices.
- MS Culture & Values: Embody our Culture and Values.