Security Engineer (Incident Response)

Join Twilio's Security Incident Response Team (SIRT) as a Security Engineer. In this role, you will lead the technical response to security events and incidents across Twilio's global infrastructure, services, and applications. You will work collaboratively with R&D Engineering and R&D Business teams to develop scalable processes and technical solutions. Your responsibilities will include documenting incidents, improving Twilio's security posture, and mentoring team members. Enjoy benefits such as work-from-home opportunities, generous annual time off, comprehensive health programs, and more.

• Lead and support the response to all security events and incidents across Twilio’s complex global infrastructure, services, and applications.
• Work cross-collaboratively to understand and help solve challenges related to a broad spectrum of threat actors and activity.
• Own the security incident lifecycle, respond to incidents and participate in on-call rotation and participate in RCAs for security incidents.
• Experience with SOAR tools and automating manual security processes
• Excellent written and verbal communication skills
• Advanced knowledge of service-oriented architectures, as well as experience with security tools and technologies fit for a cloud environment
• Subject-matter expert on security issues and technologies
• Experience with SIEM platforms and the ability to extend their functionality
• Ability to utilize AI for comprehensive, complex security incident response activities delivering high fidelity detections
• Ability to influence and build effective working relationships with every level of the organization
• Proven experience: 3+ years of security incident response in a production-cloud environment
• Experience working across a technology stack on difficult security challenges and initiatives
• Experience in either AWS, GCP, or other large cloud platform
• AI Model Security & Posture Management: Support Implementation of controls and safeguards to prevent AI vulnerabilities, such as prompt injections, model evasion, and data poisoning
• AI-Driven Threat Response: Utilize GenAI and LLM-based security use cases to rapidly interpret alerts, reduce false positives, and contextualize threat data
• Threat Intelligence Integration: Monitors external vendor data and threat intelligence to analyze trends and proactively defend against emerging risks
• Artifact & Evidence Triage: Collects intrusion artifacts and forensically sound images to analyze malware, trojans, and source code