Engineering Manager, Marketing Technology - Segmentation Platform & Insights Platform

Airbnb, founded in 2007, has grown to over 5 million hosts worldwide. They are seeking an Engineering Manager for the Segmentation and Insights Platforms, responsible for leading two teams to enhance customer engagement through advanced AI and data-driven solutions.

Responsibilities:

• Lead weekly planning, roadmap reviews, and cross-team syncs for Segmentation and Insights Platform, keeping delivery on track and stakeholders well-informed
• Run 1:1s with engineers, with intentional focus on career growth, technical skill development, and early identification of blockers
• Serve as the primary engineering DRI for cross-team dependencies — fielding requests from teams across Airbnb tech. and making clear, reasoned prioritization calls
• Partner with the Product Manager to sequence the roadmap
• Drive technical strategy for the Insights Intelligence Engine — Airbnb's emerging AI/ML anomaly and trend detection system — working across ML, Data Engineering, and Analytics Engineering disciplines
• Oversee the design, delivery, and operational health of production agentic systems: autonomous pipelines, LLM-orchestrated workflows, and multi-agent architectures running at Airbnb scale
• Champion AI-native development practices across both teams — from AI-assisted coding and review workflows to the use of agents in CI/CD, on-call response, and data quality monitoring
• Own the health and operational maturity of both teams: 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

Requirements:

• 9+ years of software engineering experience, with 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 — able to engage credibly in architecture and design conversations
• Experience owning cross-team platform relationships: managing inbound dependency requests, negotiating priorities, and communicating commitments with confidence
• 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
• 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