KAYAK

HQ
Stamford
Total Offices: 9
1,002 Total Employees
Year Founded: 2004

KAYAK Benefits Overview

Compensation + Benefits

Offers 401(K)

Provides a pension

Offers life insurance

Offers accidental death & dismemberment insurance

Offers company equity

Offers employee discounts

Offers performance bonuses

Offers dental insurance

Offers health insurance

Offers mental health benefits

Offers Flexible Spending Account (FSA)

Offers vision insurance

Provides family medical leave

Offers generous parental leave

Company Culture

Provides commuter benefits

Provides free snacks and drinks

Office is pet friendly

Offers a remote work program

Work-Life Balance + Wellbeing

Offers company-sponsored outings

Offers generous PTO

Provides paid sick days

Provides military leave

Provides paid holidays

Provides bereavement leave

Career Growth + Development

Provides tuition assistance

Recently posted jobs

2 Days AgoSaved
Remote or Hybrid
Office, Machaze, Manica, MOZ
Other • Travel
Lead one or more agile engineering teams for KAYAK for Business, driving backend architecture and distributed systems decisions, shipping B2B SaaS features, improving agile delivery and CI/CD, owning people management (hiring, performance, career development), and collaborating across product, design, and global engineering teams.
2 Days AgoSaved
Remote or Hybrid
Office, Machaze, Manica, MOZ
Other • Travel
Support GRC activities including risk assessments, policy management, control testing, audit coordination, BC/DR planning and testing, and customer security reviews. Maintain risk register, gather evidence, track remediation, and help automate GRC processes through scripts, APIs, or platform integrations while collaborating with engineering and security teams.
2 Days AgoSaved
Remote or Hybrid
Office, Machaze, Manica, MOZ
Other • Travel
Design, build, and operate scalable ML infrastructure and automated pipelines for training, deployment, and monitoring. Own model serving, GPU provisioning, Kubernetes autoscaling, observability, and SLOs. Enable data scientists with standardized, production-ready workflows and collaborate across ML, engineering, and operations teams.