Engineering Manager, Marketing Technology - Segmentation Platform & Insights Platform

Airbnb

1d•$212,000 - $265,000•Remote

About The Position

Airbnb is seeking an Engineering Manager for Marketing Technology, specifically focusing on the Segmentation Platform & Insights Platform. This role is part of the Marketing Technology team, which aims to drive sustainable growth for Airbnb by building a best-in-class agentic system. The team delivers personalized content and product experiences to the Airbnb community, with a long-term vision of AI autonomy. The platform integrates deeply with Airbnb's product to understand the customer journey and enable differentiated customer engagement. It also supports digital marketing channels like email, push, SMS, and digital advertising, along with the ML/AI and data platforms for their management and optimization. You will lead two closely partnered teams: the Segmentation Platform, responsible for audience infrastructure across all marketing surfaces, and the Insights Platform, providing observability and analytics for marketing teams. These teams collaborate with a shared Product Manager and other engineering teams. The Segmentation Platform is undergoing a significant evolution, including a near real-time customer segmentation architecture, on-the-fly targeting, new entity types, and deeper data infrastructure integrations. The Insights Platform is expanding to include AI/ML-driven anomaly detection and trend analysis. Both platforms are incorporating autonomous agent pipelines for complex workflows, and this role will ensure these systems are built with the rigor and reliability required for production-grade agentic systems.

Requirements

9+ years of software engineering experience.
4+ years in an engineering management role leading platform or infrastructure teams.
Demonstrated experience managing engineers across a range of seniority levels, including early-career engineers, with a track record of meaningful career growth outcomes.
Strong technical foundation in distributed data systems, backend infrastructure, or marketing/ad technology platforms.
Experience owning cross-team platform relationships: managing inbound dependency requests, negotiating priorities, and communicating commitments.
Track record of delivering complex, multi-quarter technical roadmaps in fast-moving environments.
Fluency in data-driven engineering practices: data pipelines, analytics infrastructure, observability, and operational excellence.

Nice To Haves

Experience with audience segmentation, targeting systems, or marketing data infrastructure at scale.
Familiarity with ML/AI-powered analytics systems or experience managing engineers working on applied ML workstreams.
Hands-on familiarity with agent frameworks and orchestration tooling (e.g., LangGraph, CrewAI, Autogen, or similar) and practical knowledge of where these systems break down in production.
Experience managing teams that own on-call rotations and production services with external SLAs.
Comfort navigating the intersection of engineering, data science, and analytics engineering disciplines within a single team.
Experience actively integrating AI-assisted development practices into team workflows and advocating for their adoption.

Responsibilities

Lead weekly planning, roadmap reviews, and cross-team syncs for Segmentation and Insights Platform.
Run 1:1s with engineers, focusing on career growth, technical skill development, and identifying blockers.
Serve as the primary engineering DRI for cross-team dependencies, fielding requests and making prioritization calls.
Partner with the Product Manager to sequence the roadmap.
Drive technical strategy for the Insights Intelligence Engine, Airbnb's AI/ML anomaly and trend detection system.
Oversee the design, delivery, and operational health of production agentic systems, including autonomous pipelines, LLM-orchestrated workflows, and multi-agent architectures.
Champion AI-native development practices across both teams.
Own the health and operational maturity of both teams, including on-call programs, incident retrospectives, SLO definitions, and runbook quality.
Represent both platforms in org-wide planning cycles and contribute to the broader Marketing Technology engineering strategy.