Note: The job is a remote job and is open to candidates in USA. Airbnb is a global company that connects hosts and guests for unique stays and experiences. They are seeking an Engineering Manager for the Segmentation and Insights Platform to lead technical direction, roadmap execution, and foster a culture of growth among engineers while incorporating AI-native engineering practices.
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
Skills
- 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
Benefits
- Bonus
- Equity
- Benefits
- Employee Travel Credits
Company Overview