Associate Security Detection Engineer, Signals Engineering

October 22

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GitLab

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Artificial Intelligence • Enterprise • SaaS

GitLab is the most comprehensive AI-powered DevSecOps platform, offering tools for automated software delivery, security, and compliance throughout the software development lifecycle. It provides solutions across areas such as AI-assisted development, continuous integration/continuous deployment (CI/CD), source code management, and vulnerability management. GitLab aims to simplify and accelerate software delivery by uniting development, security, and operations on a unified platform. It is particularly recognized for its AI code assistants and has been named a leader in the Gartner Magic Quadrant™ for DevOps Platforms, making it a preferred choice for many enterprises.

1001 - 5000 employees

Founded 2014

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Secondary Market on 2020-11

📋 Description

• Identify MITRE ATT&CK and top threat actor detection gaps, then write behavioral detections to close them • Use SIEM or data lake platforms like Splunk or Elastic to write and troubleshoot threat detections • Collaborate with peer GitLab teams to identify and close security observability improvement opportunities • Partner with incident response, red team, and threat intelligence teams to cross-functionally improve GitLab's detection program and coverage • Use, maintain, and build new Detection-as-Code (DaC), AI, and process efficiency automations for the signals engineering program

🎯 Requirements

• An understanding of the GitLab application (bonus points if you're comfortable detecting and hunting for attacks against GitLab or if you've maintained GitLab yourself) • SOC, incident response, or detection engineering experience • SIEM or security data lake detection and query experience • A proactive approach to detecting potentially malicious patterns and collaborating with incident response to complete incident RCAs and identify new detection opportunities • An interest in cloud technologies such as GKE, AWS, GCP, and other cloud native services (PaaS and SaaS) • An interest in learning how AI can be used for detection engineering • An interest in learning advanced detection capabilities, such as Detection-as-Code, signal vs detection development, risk-based alerting, and behavior analytics

🏖️ Benefits

• Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • Parental leave • Home office support