Partner with infra and product teams to deeply understand use case requirements and define the technical vision for the Knowledge Graph.
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.
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.
Ensure seamless, high-performance integration of the Knowledge Graph with a variety of downstream systems, including Search, Machine Learning, and Analytics.
Debug complex production issues and continuously improve system reliability, observability, and performance.

Requirements

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.
Proven success in building and maintaining high-scale distributed systems, particularly in data infrastructure, databases, or streaming platforms.
Hands-on experience with technologies like Kafka, Flink, Spark, or similar for data ingestion and processing.
Hands-on experience applying AI/ML techniques to data infrastructure problems. Experience with large language models (e.g., Claude, LLMs) for productivity is a plus.
Strong system design and debugging skills, with a focus on real-world reliability and scalability.

Benefits

This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data infrastructuredistributed systemsdata ingestiondata processingsystem designdebuggingAI techniquesML techniqueslarge language modelsreal-time processing

Soft Skills

leadershipcollaborationproblem-solvingcommunicationuser experience focus

Certifications

BS in Computer ScienceMS in Computer SciencePhD in Computer Science