Software Engineer II

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The Azure Compute team builds a fault-tolerant, distributed system on top of commodity datacenter hardware to deliver infrastructure for hosting cloud applications in virtual machines (VMs). The team creates the experience that resources are limitless, elastic, and always available.

This role is part of the Availability Platform team within Azure Compute, which focuses on ensuring every Azure virtual machine achieves a service-level agreement (SLA) of 99.99 percent or higher. Meeting this target requires innovative thinking, data-driven decisions, and intelligent automation. The team owns services that monitor the health of millions of Azure machines and the control plane services that make repair decisions. We use artificial intelligence (AI) and machine learning to build predictive failure models that proactively migrate virtual machines before failures occur, reducing customer impact and improving platform resilience.

We are also exploring generative AI to enhance diagnostics, automate root cause analysis, and accelerate incident resolution. Collaboration with data scientists and AI researchers enables us to continuously evolve the platform with smarter, self-healing capabilities. As a Software Engineer II, you will design and deliver services architecture at hyperscale, work on incremental development with high quality, and adapt quickly to customer feedback while integrating advanced AI technologies.

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.

Required Qualifications

• Bachelor's Degree in Computer Science or related technical field AND technical engineering experience with coding in languages including, but not limited to, C,Rust, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

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

• Bachelor's Degree in Computer Science
  • OR related technical field AND technical engineering experience with coding in languages including, but not limited to, C, Rust, C++, C#, Java, JavaScript,
  • OR Python
  • OR Master's Degree in Computer Science or related technical field AND technical engineering experience with coding in languages including, but not limited to, C,Rust, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Ability and passion for designing and building highly available distributed systems at scale.
• Ability to exercise sound judgment in ambiguous situations.
• Experience with agile methodologies and willingness to adopt them

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• Partners with appropriate stakeholders spanning across teams and orgs to determine project requirements. Leads the design and architecture of change management features and services in Azure Compute
• Identifies dependencies and authors design documents for features and services. Leverages expertise with appropriate stakeholders to develop project plans, release plans, and work items.
• Develops high quality, extensible, maintainable code and coaches others to do the same. Supports livesite as Designated Responsible Individual (DRI), mentoring engineers across products/solutions, working on-call to monitor system/product/service for degradation, downtime, or interruptions.
• Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale and shares knowledge with other engineers.
• Collaborates with data scientists and ML engineers to design and integrate predictive models that proactively detect hardware anomalies and trigger live migrations, improving VM uptime and SLA compliance.
• Leads initiatives to embed AI-driven diagnostics and root cause analysis into availability services, reducing time-to-resolution for incidents and improving operational efficiency. Drives the adoption of generative AI tools to automate documentation, incident summaries, and engineering workflows, enhancing team productivity and knowledge sharing.
• Partners with platform teams to build intelligent observability pipelines that leverage anomaly detection and trend analysis for early warning systems. Evaluates and integrates large-scale AI models into control plane services to enable smarter, context-aware repair decisions across millions of Azure VMs.