Senior Engineering Manager, AI Platform

<p>Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!</p> <p>At Duolingo, you’ll join a team that cares about finding <a href="https://blog.duolingo.com/tag/engineering/?utm_source=greenhouse.com&amp;utm_medium=referral&amp;utm_campaign=engblog_gh_091224">innovative solutions to complex technical problems</a>, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful.&nbsp;</p> <p>Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.</p> <hr> <p style="text-align: left;"><strong>About the role...</strong></p> <p>As the manager and team lead of the new AI Tooling and Ecosystem Team, you will lead the development of the suite of tools and services that power Duolingo's use of AI in the product. You'll lead a team of 5-6 engineers to design systems for managing datasets, evaluating the performance of AI models, and building AI workflows. You will help shape how Duolingo builds features using AI, enabling teams to easily define quality metrics, combine human and AI feedback, and compare model performance. We're looking for an engineering manager who has experience building AI products or infrastructure and is excited to play a central role in shaping the future of AI at Duolingo!</p> <p><strong>🧠&nbsp; You will...</strong></p> <ul> <li>Drive development of tools and services that empower Duolingo's product teams to easily and effectively build AI-powered features and workflows.</li> <li>Manage our shared systems and workflows for AI-related datasets, prompts, and evaluations (both human and LLM-as-a-judge).</li> <li>Build processes that allow teams to define success criteria for their AI use-case, identify the most appropriate models, and construct feedback loops for prompt optimization.</li> <li>Streamline common AI development flows so that teams with varying levels of AI expertise can build out AI systems quickly.</li> <li>Collaborate closely with the AI Core Infrastructure Team to ensure that AI workflows are reliable, measurable, and cost efficient.</li> <li>Partner with AI, Product, Data Science, and Platform leaders to build out new AI tooling that supports common use-cases.</li> <li>Own multi‑quarter roadmaps and cross‑functional alignment that increase AI feature velocity and measurable product impact across Duolingo.</li> </ul> <p>&