The Staff Engineer - AI Infrastructure Reliability role at Microsoft involves designing and implementing reliable engineering platforms and developer tooling for AI services. The position is part of the AI Infrastructure Engineering Systems team, which focuses on building cloud platforms and infrastructure for AI workloads. This hands-on role includes responsibilities across architecture, testing, deployment, and operations for large-scale AI systems. The engineer will work closely with multidisciplinary teams to enhance system reliability and developer efficiency.

• Bachelor's Degree in Computer Science or related technical field and 4+ years of technical engineering experience with coding in languages such as C, C++, C#, Java, JavaScript, or Python.
• Master's Degree in Computer Science or related technical field and 6+ years of technical engineering experience with coding in languages such as C, C++, C#, Java, JavaScript, or Python, or Bachelor's Degree in Computer Science or related technical field and 8+ years of technical engineering experience with coding in languages such as C, C++, C#, Java, JavaScript, or Python.
• Experience reading, writing, and debugging high-quality production code across a large, complex codebase for internet-scale services, distributed systems, or compute platforms.
• Experience building automated validation frameworks and developer-productivity tools.
• Experience serving as a technical lead, mentoring engineers, and executing multi-team engineering initiatives.
• Experience with AI training and inference infrastructure, incident management, and reliability measures such as TTD, TTM, and TTR.

• Design, build, and optimize components of distributed AI platforms to improve availability, performance, scalability, reliability, and cost efficiency.
• Lead incident-management efforts and engineer technical solutions that systematically reduce Time to Detect (TTD), Time to Mitigate (TTM), and Time to Resolve (TTR) across AI training and inference workloads.
• Build and scale automated validation frameworks and test suites that identify regressions early and maintain system stability.
• Implement graphics processing unit (GPU) and compute fleet optimizations that improve resource utilization, throughput, and operational efficiency at scale.
• Develop platform services, internal tools, and automation that streamline engineering workflows, improve developer velocity, and raise code quality standards.
• Write production code, build telemetry and observability tools, and debug complex system issues to resolve root causes and prevent incident recurrence.
• Provide technical leadership, mentor engineers, and lead multi-team initiatives across infrastructure, security, networking, and service teams.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.