Detection & Response Engineer

xAI xAI · AI Frontier · Palo Alto, CA · Information Security

This role is for a Detection & Response Engineer on the security team at xAI, focusing on safeguarding cloud-native and AI-focused infrastructure. Responsibilities include monitoring security alerts, investigating incidents, developing detection rules, and responding to threats. The role requires experience in security operations, incident response, SIEM platforms, and cloud environments, with a preference for experience with AI/ML security implications and leveraging AI for threat detection.

What you'd actually do

  1. Monitor and analyze security alerts and logs to identify potential threats and anomalies
  2. Develop, implement, and maintain detection rules and correlation logic in our SIEM platform
  3. Conduct thorough investigations of security incidents, performing root cause analysis and impact assessments
  4. Lead incident response efforts, coordinating with relevant teams to contain and mitigate threats
  5. Create and maintain incident response playbooks and runbooks

Skills

Required

  • Bachelor's degree in Computer Science, Cybersecurity, or a related field
  • 3-5 years of experience in security operations, incident response, or a similar role
  • Strong understanding of cybersecurity principles, attack techniques, and defensive strategies
  • Proficiency in at least one scripting language (e.g., Python, Rust) for automation and tool development
  • Experience with SIEM platforms and log analysis tools
  • Familiarity with cloud environments (e.g., AWS, GCP, Azure) and their security features
  • Knowledge of network protocols, system administration, and common attack vectors
  • Strong analytical and problem-solving skills with attention to detail
  • Excellent communication skills and ability to work effectively under pressure

Nice to have

  • Relevant security certifications (e.g., GCIH, GCIA, SANS)
  • Experience with threat intelligence platforms and their integration into detection processes
  • Familiarity with AI/ML security implications, particularly those outlined in the OWASP LLM Top 10
  • Knowledge of software supply chain security and SBOM analysis
  • Experience with containerized environments and Kubernetes security
  • Experience in building custom security tools or integrations to enhance detection and response capabilities
  • Interest in leveraging AI to improve threat detection and automate response processes
  • Contributions to open-source security projects or threat research
  • Experience with digital forensics and malware analysis

What the JD emphasized

  • AI/ML security implications
  • OWASP LLM Top 10
  • leveraging AI to improve threat detection and automate response processes