Tinder brings people together. With tens of millions of users, hundreds of millions of downloads, 2 billion swipes per day, 20 million matches per day and a presence in every country on earth, our reach is expansive—and rapidly growing.

We’re looking for a Security Engineer to help scale our Security Monitoring and Incident Response team. The right candidate will have experience with various log aggregation and SIEM technologies, as well as familiarity with handling investigations into potential security-related incidents. In this position, you’ll be building and securing our platform, help future Tinder users make better matches, engage more effectively, and generally make the world a better place!

We have openings in our Los Angeles headquarters or Palo Alto office!

Responsibilities:

• Manage and maintain log aggregation and SIEM technologies to ensure all systems and applications are accurately logging and examined for signs of abuse or IOCs
• Research open-source intelligence sources for additional IOCs to integrate into SIEM technologies
• Investigate potential security incidents and serve as initial incident responders
• Create dashboards and custom queries to search for suspicious activity or research known incidents
• Maintain Monitoring and Incident Response policies, procedures and documentation of investigations
• Manage internal communications and escalations for any ongoing investigations

What we’re looking for:

• 3-5 years of experience in Incident Response
• Proficiency administrating and operating within Linux systems
• Experience working in an AWS environment and/or strong knowledge of AWS
• Understanding of MacOS system internals
• Experience with digital forensics, binary analysis and/or examining network traffic
• Experience with large-scale log aggregation and SIEM technologies, such as ELK, Graylog, Splunk, AlienVault, or ArcSight
• Basic scripting capabilities for API client creation and data processing utilizing BASH, or, Python, or, GO

Bonus if you have:

• Working knowledge of Docker and Kubernetes
• Exposure to automated data analysis (Machine Learning)

As an equal opportunity employer, we are committed to diversity in the workforce. In accordance with applicable law, we prohibit discrimination against any applicant or employee based on any legally recognized basis, including, but not limited to; race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 and over), national origin or ancestry, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed service member status or any other status protected by federal, state or local law.