Define benchmarking, workload characterization, and performance evaluation frameworks used to influence platform and infrastructure decisions across compute, gpu, memory, storage, networking, and accelerator technologies. Lead deep technical investigations into performance, efficiency, and scalability challenges across large-scale distributed systems and AI-powered services. Partner with Azure, infrastructure, and platform engineering teams to evaluate emerging hardware technologies and translate platform capabilities into meaningful customer and business impact. Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Proven track record leading performance, systems, infrastructure, or hardware strategy initiatives for large-scale cloud services. Deep understanding of distributed systems, computer architecture, performance engineering, benchmarking, and workload analysis. Experience using data, experimentation, and technical analysis to influence platform, architecture, or infrastructure investment decisions. Demonstrated ability to lead cross-organizational technical efforts and influence senior engineering leaders. Experience applying AI to engineering workflows, performance analysis, diagnostics, optimization, or operational decision-making. Experience with AI infrastructure, large-scale inference workloads, retrieval systems, agent platforms, or Copilot-style architectures. Experience evaluating emerging hardware platforms and translating hardware capabilities into product and platform advantages. Experience building AI-assisted engineering systems for diagnostics, performance analysis, optimization, or operational intelligence.
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