Senior Engineering Manager, Monetization

Duolingo•New York, NY

About The Position

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! At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, 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. Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world. Duolingo's Monetization pillar builds the systems that fund our mission — from subscription packaging and advertising to ML-powered personalization, performance marketing, and beyond. As a Senior Engineering Manager, you'll lead a cross-functional product engineering team working on high-impact, revenue-generating systems that help Duolingo grow sustainably while keeping the product playful, transparent, and learner-first. Your team will build and scale systems across ads and paid growth — building signal and audience pipelines, powering creative experimentation, improving ad quality, optimizing budget allocation, and strengthening attribution and ROI guardrails. You'll partner closely with product, design, data science, machine learning, and marketing to define strategy and deliver results. Just as importantly, you'll create an environment where engineers do the best work of their careers — coaching, developing talent, and fostering a high-performing team culture.

Requirements

2+ years of experience leading, managing, and building a team of software engineers.
A track record of owning multi‑engineer, multi‑week technical projects to successful outcomes in a highly experimental, data‑driven environment.
Strong product instincts and excellent written/verbal communication, with experience aligning diverse stakeholders across engineering, product, design, and analytics.
Experience working closely with data, experimentation, or machine learning teams to inform prioritization and ship measurable impact (direct ML expertise not required).
Demonstrated ability to raise the bar on engineering practices for reliability, scalability, and observability.

Nice To Haves

Prior experience with advertising platforms, ad tech integrations, or building ad surfaces in mobile apps.
Experience improving ad quality and monetization through experimentation, targeting, or programmatic levers, in partnership with business teams.
Familiarity with COPPA‑compliant or kid‑friendly ad solutions and the trade‑offs of untargeted inventory.
Background collaborating with sales/biz ops on direct or programmatic campaigns and translating market feedback into product improvements.
Experience leading teams that span multiple platforms (iOS, Android, backend) and partnering on ML‑powered personalization within consumer apps.

Responsibilities

Co-lead a cross-functional pod with Product and Marketing to define strategy, success metrics, and an execution roadmap for Duolingo’s performance marketing engine, aligned to ROI guardrails and retained-user growth goals.
Build and evolve the engineering systems that power paid growth at scale: creative experiment frameworks, audience/signal ingestion and privacy-safe list management, budget and bid optimization tooling, and reliable attribution and reporting pipelines.
Collaborate with data science and ML partners to design experiments, apply personalization/targeting, and translate insights into product improvements and bookings growth.
Own planning and execution for projects that directly impact revenue; identify the right team‑level metrics to optimize and protect delivery through clear milestones and risk management.
Bring both technical and product perspectives to new ideas, enabling rapid hypothesis testing without sacrificing reliability, observability, or long‑term maintainability.
Set and uphold engineering quality standards and practices that improve reliability, scalability, and operability across Ads systems.