Site Reliability Engineer II

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Join the Azure Specialized AI Infrastructure team in India to drive advancements in Artificial Intelligence (AI) and support high-performance infrastructure for generative AI workloads. As a Senior SRE, you will automate and maintain large-scale distributed systems powering latest AI applications and machine learning models. Your primary focus will be on the reliability, scalability, and performance of AI infrastructure, ensuring seamless operations for mission-critical AI services. The role emphasizes a start-up mindset, collaboration, and customer advocacy.

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/Minimum Qualifications:

• 4+ years technical experience in software engineering, network engineering, or systems administration
  
  • OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 1+ year(s) technical experience in software engineering, network engineering, or systems administration
  • OR Master's Degree in Computer Science, Information Technology, or related field.
• Proven ability to modify componentized, well-architected infrastructure software and collaborate across teams.
• Proficient technical design, analytical, and debugging abilities.
• 1+ years experience with incident management and reliability engineering in cloud or AI environments.
• Excellent interpersonal, communication, and collaboration skills.

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.

Additional or Preferred Qualifications:

• 5+ years technical experience in software engineering, network engineering,
  
  • OR systems administration
  • OR Bachelor's Degree in Computer Science, Information Technology,
  • OR related field AND 2+ years technical experience in software engineering, network engineering,
  • OR systems administration
  • OR Master's Degree in Computer Science, Information Technology,
  • OR related field AND 1+ year(s) technical experience in software engineering, network engineering,
• 1+ year(s) people management experience.
• Experience in distributed systems and/or cloud platforms (Azure, Kubernetes, Docker, containers ecosystem).
• Experience with GPUs, InfiniBand, or similar high-performance technologies.
• Proficiency in RDMA (Remote Direct Memory Access), MPI (Message Passing Interface), and high-performance computing architecture.
• Proficient in scripting (PowerShell, Shell script, etc.) and deep expertise in Linux.

#azurecorejobs

• Reliability: Ensure the reliability, scalability, and security of AI infrastructure supporting HPC & AI workloads.
• Incident Management: Lead incident response, root cause analysis, and continuous improvement to minimize downtime and optimize service availability.
• Performance Optimization: Identify and resolve bottlenecks in compute, storage, networking, and specialized hardware (GPUs, InfiniBand) to enhance AI system performance.
• Infrastructure Automation: Develop and maintain automation tools for deployment, monitoring, predictive analysis and management of AI infrastructure, including containerized environments (Kubernetes, Docker).
• Technical Leadership: Provide technical guidance in cloud and AI infrastructure technologies, collaborating with cross-functional teams to drive innovation and best practices.
• Customer Advocacy: Act as a customer advocate, focusing on service excellence and live site reliability for AI workloads.
• Research & Innovation: Stay informed on emerging AI infrastructure technologies and industry trends, recommending adoption where beneficial.