Senior Software Engineer

Microsoft•Redmond, WA

1d•$119,800 - $234,700

About The Position

The Windows + Devices Fundamentals team improves the reliability, performance, battery life, and sustainability of Windows devices. Our work spans hardware, silicon, firmware, drivers, the operating system, and applications, with the goal of making outstanding fundamentals a defining characteristic of Windows PCs. We are looking for a Senior Software Engineer with solid systems and performance experience to identify performance opportunities and drive measurable improvements across Windows and the broader device ecosystem. In this role, you will combine deep performance analysis, large-scale telemetry, benchmarking, and AI-assisted engineering to understand where users experience performance bottlenecks, quantify regressions and affected scenarios, isolate root causes, and translate those insights into measurable improvements. You will work with rich telemetry and trace data, investigate complex system behavior across hardware and software boundaries, and build workloads and benchmarks that expose meaningful performance differences across devices and platforms. You will also help advance how performance engineering is done, using AI together with performance data, diagnostic tools, and source-code context to accelerate investigations and identify optimization opportunities at scale. This role is for an engineer who enjoys going deep into systems behavior and wants to help shape the next generation of AI-powered performance engineering. 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.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience.
Demonstrated software engineering and debugging skills, with experience investigating complex systems or application behavior.
Experience with performance analysis, profiling, telemetry, diagnostics, benchmarking, or related systems-analysis techniques.
Ability to analyze complex technical data, form testable hypotheses, and translate findings into engineering actions.
Knowledge of operating-system fundamentals, including thread scheduling, memory management, storage/I/O, synchronization, resource management, or other low-level systems concepts.
Experience with Windows performance and diagnostic technologies, such as ETW, WPR/WPA, WinDbg, or comparable profiling and tracing systems.
Experience using large-scale telemetry and data-analysis platforms, including Kusto or similar technologies, to identify trends, regressions, and performance opportunities.
Experience designing performance workloads, benchmarks, experiments and interpreting results across hardware, software, or operating-system configurations.
Experience applying AI-assisted engineering tools to analyze technical data, source code, traces, or complex engineering problems.
Experience building analysis tools or automation that combines telemetry, profiling information, source code, and engineering context.
Experience with statistical analysis and experimental methodology, including establishing baselines, evaluating measurement quality, and distinguishing meaningful performance changes from workload or measurement variability.
Experience investigating complex problems across hardware, firmware, drivers, operating systems, and applications.
Experience collaborating with OEMs, IHVs, ISVs, silicon partners, or other external engineering organizations on complex technical investigations and product improvements.

Nice To Haves

Bachelor's degree in Computer Science or a related technical discipline and 4+ years of technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience.

Responsibilities

Perform deep performance investigations using telemetry, ETW traces, profiling, critical-path analysis, and system-level debugging to identify bottlenecks spanning CPU, memory, storage/I/O, thread scheduling, and responsiveness.
Turn large-scale telemetry and trace data into actionable engineering insights, moving from population-level signals and regressions to representative traces, root cause, source-code attribution, and quantified opportunities for performance improvement.
Advance AI-powered performance engineering by combining performance data, trace evidence, profiling results, source code, and engineering context with AI to accelerate analysis and uncover actionable optimization opportunities at scale.
Develop tools and analysis techniques that scale deep performance analysis with AI, while applying rigorous validation to ensure insights are grounded in measured system behavior and lead to meaningful engineering improvements.
Design representative workloads and benchmarks to characterize real-world performance, establish trustworthy baselines, account for measurement variability, and enable rigorous comparisons across Windows releases, silicon platforms, device configurations, and alternative platforms.
Drive leading performance and resource-efficiency investigations, understanding system behavior across device classes, hardware configurations, and memory-constrained systems and identifying opportunities to deliver differentiated Windows experiences.
Translate analysis into engineering impact by developing optimization hypotheses, validating them experimentally, quantifying tradeoffs, and working with component owners to turn findings into measurable product improvements.
Partner deeply with engineering teams, OEMs, silicon vendors, IHVs, and ISVs to investigate complex performance problems, influence technical decisions, and drive optimizations spanning hardware, firmware, drivers, the operating system, and applications.
Build trusted technical partnerships with internal and external engineering teams, using data and deep technical analysis to align on root cause, evaluate tradeoffs, and drive performance improvements through delivery.