Senior Engineering Manager, Monetization

Duolingo Duolingo · Consumer · New York, NY +1 · Software Engineering

Senior Engineering Manager for Duolingo's Monetization pillar, leading a cross-functional team to build and scale revenue-generating systems including subscription packaging, advertising, ML-powered personalization, and performance marketing. The role involves defining strategy, overseeing engineering systems for paid growth, collaborating with data science and ML partners, and ensuring engineering quality.

What you'd actually do

  1. 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.
  2. 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.
  3. Collaborate with data science and ML partners to design experiments, apply personalization/targeting, and translate insights into product improvements and bookings growth.
  4. 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.
  5. Bring both technical and product perspectives to new ideas, enabling rapid hypothesis testing without sacrificing reliability, observability, or long‑term maintainability.

Skills

Required

  • 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 have

  • 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.

What the JD emphasized

  • high-impact, revenue-generating systems
  • performance marketing engine
  • ROI guardrails
  • paid growth at scale
  • reliable attribution and reporting pipelines
  • ML partners
  • measurable impact
  • reliability, scalability, and observability
  • ad quality
  • monetization through experimentation, targeting, or programmatic levers