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• Pipeline Scale & Automation: Architect, scale, and optimize high-throughput CI/CD pipelines (Azure DevOps / GitHub Actions) to automate the generation, patching, and validation of Windows OEM factory images across all Surface product lines.
• OEM Compliance & Image Engineering: Ensure adherence to the Windows OEM Imaging Guide, managing complex image configurations—including driver injection, language packs, provisioning packages, and customized Out-of-Box Experiences (OOBE).
• Distributed Systems Architecture: Design resilient, low-latency infrastructure to support large-scale binary artifacts, distributed caching, and parallelized test execution across hybrid environments.
• Intelligent DevOps & AI Integration: Leverage Azure AI services (e.g., Azure OpenAI, Cognitive Services, ML pipelines) to enable intelligent error analysis, predictive failure detection, and automated quality gates.
• Cross-Functional Collaboration: Partner with Surface hardware, Windows OS, security, and global manufacturing teams to streamline the end-to-end code-to-factory lifecycle.
• Engineering Excellence & Observability: Drive robust telemetry, observability, and alerting across pipelines; champion infrastructure-as-code (IaC) best practices and mentor engineers to build scalable, maintainable systems.

• 6+ years of software engineering experience with a strong track record in CI/CD systems, automated release management, infrastructure-as-code, or systems engineering.
• Deep understanding of Windows provisioning and deployment, including WIM/FFU imaging formats, DISM tooling, Sysprep, secure boot, and the Windows OEM Imaging Guide.
• Proven experience building and operating enterprise-scale CI/CD pipelines using Azure DevOps (YAML) and/or GitHub Actions.
• Proficiency in scripting and object-oriented programming (e.g., PowerShell, C#, Python, Go) to develop custom tooling and automation frameworks.
• Strong understanding of distributed systems design principles, including scalability, reliability, and fault tolerance.
• Experience or familiarity with Azure AI services (e.g., Azure Machine Learning, Azure OpenAI) applied to telemetry analysis, log intelligence, or MLOps workflows.
• Experience with OS-level hardware bring-up, firmware (UEFI/BIOS), or factory/manufacturing execution environments.