Leads engineering teams building Segmentation and Insights Platforms for Airbnb's marketing technology, driving technical strategy, roadmap execution, and AI-native practices for real-time customer segmentation, anomaly detection, and autonomous agent systems.
212k – 265k
Remote9+ YOEEngineering Management
About the role
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 primary engineering DRI for cross-team dependencies, prioritizing requests from Airbnb tech teams.
Partner with Product Manager to sequence the roadmap.
Drive technical strategy for Insights Intelligence Engine (AI/ML anomaly and trend detection), collaborating across ML, Data Engineering, and Analytics Engineering.
Oversee design, delivery, and operational health of production agentic systems: autonomous pipelines, LLM-orchestrated workflows, multi-agent architectures.
Champion AI-native development practices: AI-assisted coding, review workflows, agents in CI/CD, on-call, data quality monitoring.
Own team health: on-call programs, incident retrospectives, SLOs, runbooks.
Represent platforms in org-wide planning and contribute to Marketing Technology engineering strategy.
Requirements
Required
9+ years software engineering experience, 4+ years engineering management leading platform/infrastructure teams.
Experience managing engineers across seniority levels, with career growth track record.
Strong foundation in distributed data systems, backend infrastructure, or marketing/ad tech platforms.
Delivering complex, multi-quarter technical roadmaps in fast-moving environments.
Fluency in data-driven engineering: data pipelines, analytics infrastructure, observability, operational excellence.
Preferred
Experience with audience segmentation, targeting systems, marketing data infrastructure at scale.
Familiarity with ML/AI-powered analytics or managing applied ML workstreams.
Hands-on with agent frameworks (e.g., LangGraph, CrewAI, Autogen) and production challenges.
Managing teams with on-call rotations and external SLAs.
Navigating engineering, data science, analytics engineering intersection.
Integrating AI-assisted development into workflows.
Skills
Distributed Data SystemsBackend InfrastructureData PipelinesAnalytics InfrastructureObservabilityAI/MLAgent FrameworksLangGraphCrewaiAutogenSLOsMarketing TechnologyAudience SegmentationTargeting Systems
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