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Site Reliability Engineer II

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 a...

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Microsoft Hyderabad, TS,IN, IN Source published Aug 31, 2026 Verified 19 hours ago
✓ 95% verification score · Source: Microsoft Careers · Always confirm final requirements on the original source.
Complete source information imported The available role or programme description, requirements, benefits and source facts were imported from the public official endpoint and formatted for reading.
Site Reliability Engineer II opportunity at Microsoft
DeadlineSat Feb 27 5:41 AM 2027
EmploymentF U L L T I M E
CountryIN

Overview

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. Master's Degree in Computer Science, Information Technology, or related field AND

Full job description

Full Job Description

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. Master'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 Bachelor's Degree in Computer Science, Information Technology, or related field AND 6+ years technical experience in software engineering, network engineering, or systems administration 8+ years of professional software engineering experience, with 5+ years in service operations, monitoring, and reliability improvement for infrastructure. 1+ years experience with incident management and reliability engineering in cloud or AI environments. Master's Degree in Computer Science, Information Technology, or related field AND 3+ years technical experience in software engineering, network engineering, or systems administration OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 5+ years technical experience in software engineering, network engineering, or systems administration OR equivalent experience. 2+ years technical experience working with large-scale cloud or distributed systems. 1+ years experience in distributed systems and/or cloud platforms (Azure, Kubernetes, Docker, containers ecosystem). 1+ years experience with GPUs, InfiniBand, or similar high-performance technologies.

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