Distributed SystemsKafkaSparkAIMachine LearningMLLarge Language ModelsClaudeAnalytics
About this role
Role Overview
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.
Tech Stack
Distributed Systems
Kafka
Spark
Benefits
This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.