Teams at KAYAK

Build and maintain full-stack web features, dynamic landing pages, APIs, backend services, integrations, and personalized marketing experiences used by millions of travelers. Responsibilities include architectural decision-making, testing, code reviews, production troubleshooting, performance and reliability improvements, cross-functional collaboration, and mentoring engineers.

Build and operate scalable machine learning infrastructure, including CI/CD, model training, deployment, serving, feature stores, registries, monitoring, and drift detection. Enable Kubernetes autoscaling and GPU-backed production, establish observability and service-level objectives, improve platform reliability, and create standardized workflows that help data scientists move models from experimentation to production.

Build and evolve shared backend platform capabilities, Java frameworks, runtime systems, and deployment infrastructure. Improve CI/CD workflows, release quality, observability, reliability, and developer velocity across engineering teams. Contribute to initiatives including Kubernetes multi-cluster deployments, web gateways, faster pod startup, secure service communication, ephemeral test environments, and AI-driven observability. Collaborate with product engineering teams, participate in design reviews, and help establish scalable backend standards.