We are hiring a Principal Tech Lead Manager to own and grow Copilot's image generation capabilities. This is a high-impact, high-ownership role at the intersection of frontier model integration, evaluation science, and product quality. This role sits at the heart of one of Copilot's most visible and fast-growing features. You will set the technical direction for image generation, lead a team of Applied AI engineers and platform engineers, and drive measurable improvements in image quality, user satisfaction, and first-run success. You will also be responsible for growing the team by identifying, recruiting, and onboarding the engineers needed to take these capabilities to the next level.

Technical Leadership & VisionDefine and own the end-to-end technical roadmap for Copilot image generation — from prompt understanding and model integration to evaluation, quality, and reliability.Establish architectural best practices for image generation pipelines, including prompt conditioning, safety filtering, multimodal grounding, and user personalization.Partner with research, product, and infrastructure teams to translate long-horizon vision into executable milestones.Serve as the primary technical decision-maker for model selection, integration approaches, and evaluation strategy.Image Generation Product & Model DeliveryLead the integration, evaluation, and launch of new image generation models and capabilities into Copilot surfaces.Drive improvements to first-run success rate, image quality, prompt adherence, and overall user satisfaction with generated images.Build and own the feedback loop from user signals to model and prompt iteration. Close the loop from production data to systematic improvements.Identify and resolve failure modes in image generation including safety gaps, quality regressions, prompt misinterpretation, and accessibility issues.Evaluation, Hillclimbing & Quality SystemsArchitect and scale evaluation frameworks purpose-built for image generation: aesthetic quality, safety, prompt fidelity, diversity, and user preference.Lead competitive benchmarking against peer systems, establishing clear metrics to track progress and signal investment areas.Run systematic hillclimbing loops across models, prompts, and post-processing strategies to drive continuous quality improvement.Build tooling that enables rapid experimentation and tight iteration cycles for the broader AI org.Team Building & People LeadershipHire, onboard, and grow a high-performing team of Applied AI Engineers and ML practitioners focused on image generation.Set clear goals and success criteria for direct reports; invest in their development through coaching, feedback, and stretch opportunities.Partner with recruiting to define hiring criteria, run structured interviews, and represent the team's needs in headcount planning.Create and maintain a culture of ownership, exper