• Engineering 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.

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.

Engineering 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 Optimization

• Integrate 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 & Infrastructure

• Develop 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 Collaboration

• Partner 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 & Compliance

• Apply Responsible AI principles, privacy safeguards, and compliance checks within .NET engineering workflows.

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in .NET and C#
  • OR equivalent experience.

• 2+ years of experience with CI/CD pipelines, containerization (Docker/Kubernetes), and Azure DevOps.
• 6+ months of experience using AI-assisted development tools (e.g., GitHub Copilot, or similar) to enhance productivity and code quality

• 2+ years of experience with distributed systems and cloud-native architectures.

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: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Exposure to AI/ML frameworks (PyTorch, TensorFlow) and AI model lifecycle.

• Knowledge of Azure AI services, OpenAI integration, and AI-driven developer tools.

• Understanding of security, compliance, and privacy in AI systems.
• Experience with YAML.

#DevDiv #DDJL #CoreAI

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.