Engineering Manager (Marketing Technology - Segmentation Platform & Insights Platform)

Role overview

Join Airbnb’s Marketing Technology team as an Engineering Manager for the Segmentation Platform and Insights Platform. You’ll set the technical direction, drive roadmap execution, and build a high-growth engineering culture while helping Airbnb move toward AI-native engineering.

Key missions & responsibilities

• Lead platform teams for Segmentation and Insights, owning roadmap execution and technical direction.
• Evolve the Segmentation Platform by building a near real-time customer segmentation architecture.
• Integrate autonomous agent pipelines into platform workflows.
• Champion AI-native development practices across both teams, including:
  • AI-assisted coding
  • Using agents in CI/CD
  • Data quality monitoring and operational excellence
• Manage cross-team platform relationships: handle inbound dependency requests, negotiate priorities, and communicate commitments.
• Lead engineers across different seniority levels, delivering meaningful career growth outcomes.

Requirements

• 9+ years software engineering experience, including 4+ years in an engineering management role leading platform/infrastructure teams.
• Fluency in data-driven engineering: data pipelines, analytics infrastructure, observability, and operational excellence.
• Proven ability to deliver complex multi-quarter technical roadmaps in fast-moving environments.
• Strong technical foundation in distributed data systems, backend infrastructure, or marketing/ad tech platforms; able to contribute credibly to architecture/design.
• Experience with audience segmentation/targeting systems or marketing data infrastructure at scale.
• Experience integrating ML/AI-powered analytics systems or managing teams working on applied ML.
• Hands-on familiarity with agent frameworks/orchestration tools (e.g., LangGraph, CrewAI, Autogen) and understanding of production failure modes.
• Experience managing teams that own on-call rotations, production services, and meet external SLAs.
• Ability to navigate the intersection of engineering, data science, and analytics engineering.
• Experience adopting AI-assisted development in real team workflows.

Nice-to-haves

• Practical experience with agent orchestration systems used in production for CI/CD and data quality monitoring.