Senior Software Engineer, Knowledge Graph

Airbnb Airbnb · Consumer · United States · Software Engineering

Senior Software Engineer on the Knowledge Graph team within Airbnb's Search organization. This role focuses on building and scaling the core data infrastructure for the graph system, which powers search, recommendations, and personalization. Responsibilities include designing and scaling data ingestion and consumption pipelines, ensuring high-performance integration with downstream systems like ML and Analytics, and improving system reliability and observability. Requires experience with distributed systems, data infrastructure, and applying AI/ML techniques to data infrastructure problems.

What you'd actually do

  1. Partner with infra and product teams to deeply understand use case requirements and define the technical vision for the Knowledge Graph.
  2. Design, build, and scale the end-to-end (E2E) Travel Graph infrastructure, prioritizing a robust and easy-to-use platform for all consumers and producers of graph data.
  3. Lead the large-scale data onboarding strategy, focusing on a user-friendly experience for ingesting diverse data sources (1st and 3rd party data, derived signals) via both batch and Near Real-Time (NRT) pipelines.
  4. Ensure seamless, high-performance integration of the Knowledge Graph with a variety of downstream systems, including Search, Machine Learning, and Analytics.
  5. Debug complex production issues and continuously improve system reliability, observability, and performance.

Skills

Required

  • BS/MS/PhD in Computer Science, a related field, or equivalent work experience
  • 5+ years of industry experience with a BS/Masters, and 3+ years with a PhD
  • building and maintaining high-scale distributed systems
  • data infrastructure
  • databases
  • streaming platforms
  • Kafka
  • Flink
  • Spark
  • system design
  • debugging skills
  • real-world reliability and scalability

Nice to have

  • applying AI/ML techniques to data infrastructure problems
  • large language models (e.g., Claude, LLMs) for productivity

What the JD emphasized

  • strong industry experience in building large-scale infrastructure systems
  • scalable data ingestion & consumption
  • system performance in production environments
  • high-scale distributed systems
  • data infrastructure
  • streaming platforms
  • applying AI/ML techniques to data infrastructure problems