Role Description

The Detection and Response Team (DART) is looking for a Security Engineer with experience performing detection and incident response engineering. You will operate and build the tools and detections to catch the next incident, contain it, and keep Dropbox worthy of trust!

We are a multi-disciplinary team with a wide variety of skills and responsibilities including Linux, macOS, and Windows systems security, network security, and detection and response capabilities. We have many greenfield opportunities to apply your prior experience and vision to improve Dropbox’s detection and response program!

Responsibilities

• Develop, apply, and refine detection and incident response playbooks
• Perform oncall duties triaging detection and incident response events
• Analyze data from disparate sources, correlating noise into security events
• Improve detection workflows with automation and alert enrichments
• Write detection rules to identify threats specific to our environment
• Share knowledge and experience with peer teams and DART engineers

Minimum Qualifications

• 4+ years experience as a security engineer in related domains
• Experience in operational teams or responsible as the first responder to security incidents
• Knowledge of operating systems, file systems, and memory on OS X, Linux, Windows, or iOS/Android.
• Coding or scripting proficiency in one or more languages
• Experience improving operational teams capabilities/KPI's
• Practical experience with attacker tactics, techniques, and procedures

Preferred Qualifications

• Experience and knowledge across multiple security domains, but with expertise in detection engineering, digital forensics, incident response, threat intelligence, or malware analysis.
• Recent digital forensic experience including memory or live analysis of macOS, Linux, Windows, or iOS/Android systems
• Experience as an incident responder responsible for running large scale incidents
• Demonstrated engagement in the security community through talks, papers, or code
• Previous experience applying statistical and machine learning analysis in the detection domain