Security Engineer, Incident Response

Details

• Lead and support the response to all security events and incidents across Twilio’s complex global infrastructure, services and applications.
• Be responsible for documentation of incidents and projects you work on and craft best practices as runbooks and standard operating procedures to share knowledge across teams.
• Work cross-collaboratively to understand and help solve challenges related to a broad spectrum of threat actors and activity.
• Work to improve Twilio’s security and reliability posture by driving identified betterments from security events and incidents.
• Rapidly acquire new technical skills and knowledge in a fast-paced, highly disruptive industry environment.
• Own the security incident lifecycle, respond to incidents and participate in on-call rotation and participate in RCAs for security incidents.
• Build, cultivate, and maintain positive relationships with internal customers to identify and facilitate solutions to increase the impact of the team’s work.
• Provide mentorship, support, and care for the team in a way that enables long-term career development, happiness, and success at scale.
• Proven experience: 3+ years of security incident response in a production-cloud environment
• Subject-matter expert on security issues and technologies
• Ability to utilize AI for comprehensive, complex security incident response activities delivering high fidelity detections
• Advanced knowledge of service-oriented architectures, as well as experience with security tools and technologies fit for a cloud environment
• Experience working across a technology stack on difficult security challenges and initiatives
• Experience with SIEM platforms and the ability to extend their functionality
• Experience with SOAR tools and automating manual security processes
• Experience in either AWS, GCP, or other large cloud platform
• Excellent written and verbal communication skills
• Ability to influence and build effective working relationships with every level of the organization.
• 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
• Artifact & Evidence Triage: Collects intrusion artifacts and forensically sound images to analyze malware, trojans, and source code.
• Threat Intelligence Integration: Monitors external vendor data and threat intelligence to analyze trends and proactively defend against emerging risks.