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As a Software Engineering Manager in Windows Ecosystem & Commercial Engagements (WECE), you will hire and direct a talented team of engineers on a mission to create & operate a trusted decision-intelligence system. This opportunity will allow you to deliver actionable insights and enable rapid action by your peer teams. You will be able to demonstrate that your team is at the cutting edge of AI-assisted engineering while delivering a useful system used every day to improve the speed and agility of our broader team.
Job Responsibility:
Guides partnership with appropriate stakeholders (e.g., security, privacy, responsible AI) to determine user requirements within and across teams
Guides teams and leads identification of dependencies and the development of design documents for a product, application, service, or platform
Optimizes, debugs, refactors, and reuses code to improve performance and maintainability, effectiveness, and return on investment (ROI)
Guides team to drive multiple group's project plans, release plans, and work items in coordination with appropriate stakeholders (e.g., project managers)
Own delivery of full-stack services that combine product engineering with data/ML capabilities (data ingestion, feature engineering, model integration, evaluation, and production operations)
Deliver services and data workflows that synthesize multi-source signals into high-quality, timely insights for engineering and business stakeholders
Requirements:
Bachelor's Degree in Computer Science, or related technical discipline AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
3+ years engineering management experience leading managers and/or senior ICs
Developed and released LLM-based systems to production with production runtime of 6+ months with significant usage
Experience building on Azure’s data + AI stack to deliver production-grade systems (data engineering, model integration, evaluation, and operations)
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Hands-on experience using AI-assisted development tools in production engineering environments (e.g., LLM-powered IDE workflows, code generation, automated refactoring/testing) and the ability to operationalize them into consistent team practices
Experience leading teams across software + data/analytics/ML boundaries, including shared ownership models and clear data contracts
Experience designing multi-agent architectures and evaluation-driven development workflows
Practical application of automated evaluation harnesses, quality gates, and monitoring to improve agent outputs over time