Senior Software Engineer

Lead the definition of Windows Fundamentals metrics, success criteria, cohort strategies, and measurement frameworks across reliability, performance, responsiveness, power, battery life, memory, and storage.

Architect, build, and operate scalable backend services and data pipelines for telemetry ingestion, transformation, orchestration, storage, health monitoring, diagnostics, and engineering workflows.

Establish high standards for service reliability, security, compliance, observability, data quality, schema evolution, deployment safety, incident response, and operational support.

Analyze large-scale telemetry, diagnostic signals, and traces to identify trends, anomalies, regressions, causal factors, and customer impact.

Lead investigations into metric movements using statistical methods, experimentation, systems debugging, and performance-analysis tools; translate findings into prioritized engineering actions.

Design and deliver automation, AI-assisted analysis, dashboards, alerts, and diagnostic workflows that detect issues earlier and reduce manual engineering effort.

Provide technical leadership across Windows engineering, data science, security, silicon, OEM, and service teams; mentor engineers and influence service architecture, measurement strategy, and investment decisions.

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.

These requirements include but are not limited to the following specialized security screenings: Applicants must have at least six years of software engineering experience and a bachelor's degree in Computer Science or a related technical discipline.

Equivalent practical experience is accepted in place of the degree.

Three or more years of experience in backend service development, data engineering, distributed systems, large-scale analytics, systems analysis, or related work.

Demonstrated success architecting, developing, deploying, and operating reliable production services, data pipelines, telemetry systems, analytics, or engineering platforms.

Solid software design, programming, debugging, statistical reasoning, and problem-solving skills; ability to lead ambiguous technical work and influence decisions through evidence.

with operating systems, Windows internals, distributed services, system-level development, performance engineering, data engineering, or large-scale fleet analytics.

defining organizational KPIs, establishing baselines and cohorts, investigating regressions, and communicating insights to engineering and leadership audiences.

designing scalable telemetry schemas, service APIs, orchestration systems, data-quality controls, monitoring and alerting, anomaly-detection systems, or automated diagnostic workflows.

with Kusto, Azure services and data platforms, privacy-conscious telemetry, secure service operations, statistical analysis, machine learning, or AI applied to engineering analysis and diagnostics.