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As Microsoft continues to push the boundaries of AI, we are on the lookout for seasoned engineering leaders to help shape the future of our AI products and organization. Our vision is bold and broad — to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It's also inclusive: we aim to make AI accessible to all — consumers, businesses, developers — so that everyone can realize its benefits. Microsoft AI (MAI) is seeking an experienced Senior Engineering Leader to build, scale, and run a high-performing engineering organization responsible for Copilot AI Evaluation. This is a role for a proven people leader who has built and managed multi-team organizations — someone who has hired and developed engineering managers, set organizational strategy, and delivered large-scale technical programs across multiple workstreams. You will own the engineering vision for LLM evaluation at Copilot, partnering directly with senior Eng and Product leadership to define priorities, drive execution, and raise the bar on engineering excellence. We are looking for a leader who combines deep technical judgment with a passion for growing people and building high-trust, high-velocity teams.
Job Responsibility:
Build and lead a multi-team engineering organization (30+ engineers across multiple teams), including hiring and developing engineering managers who lead their own teams
Set the technical and organizational strategy for Copilot AI Evaluation and response quality, aligning with MAI's broader product and engineering vision
Partner with senior Eng and Product leadership (Partner+ level) to define priorities, influence roadmaps, and drive cross-organizational initiatives
Own end-to-end delivery of evaluation platforms, novel evaluation techniques, and agentic solutions for measuring and improving Copilot quality at scale
Recruit, develop, and retain world-class engineering talent — building a culture of technical excellence, accountability, and continuous learning
Drive operational rigor: establish engineering processes, quality bars, and delivery cadences that enable predictable, high-quality execution across multiple concurrent workstreams
Navigate ambiguity and make high-judgment tradeoff decisions on technology, staffing, and investment priorities in a fast-moving AI landscape
Foster a diverse, inclusive team culture where engineers at all levels can do their best work and grow their careers
Embody our Culture and Values.
Requirements:
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 OR equivalent experience
Demonstrated track record of building and scaling engineering organizations (hiring teams from scratch, structuring orgs, growing managers)
Experience delivering large-scale software systems in AI, machine learning, or related fields
Experience managing organizations of 30+ engineers across multiple teams and workstreams
Deep expertise in LLM evaluation, AI quality measurement, or ML infrastructure at scale
Track record of partnering with senior leadership (VP/CVP level) to set strategy and drive cross-organizational programs
Experience recruiting and developing senior engineering talent (principal engineers, engineering managers) in a competitive market
Proven ability to operate effectively in fast-paced, ambiguous environments — comfortable making decisions with incomplete information and course-correcting quickly
Strong technical judgment: ability to evaluate architectural tradeoffs, assess technical risk, and guide teams toward sound engineering decisions without needing to write the code yourself
Experience leading distributed or multi-site engineering teams.
Nice to have:
Bachelor's Degree in Computer Science or related technical discipline AND 12+ years of technical engineering experience, including 6+ years of engineering management experience with direct reports who are themselves people managers (managing managers)
Master's Degree or PhD in Computer Science or related technical field AND 15+ years of engineering experience, including 8+ years of people management experience.