Staff Enterprise Security Engineer, AI Security

Twilio is a communications technology company empowering businesses and developers to create personalized customer experiences. The Staff Enterprise Security Engineer will provide technical leadership for securing the enterprise AI ecosystem by designing security architectures, building technical guardrails, managing AI-related risks, and advising stakeholders.

Responsibilities:

• Design and implement secure reference architectures for Enterprise AI platforms that secures every Twilion’s engagement with them, ensuring data integrity, regulatory compliance, and resilience against evolving AI threats
• Establish a definitive framework for AI vetting, driving the cultural and policy shifts needed to institutionalize this strategic mindset across the organization
• Collaborate with cross functional partners to develop and set the long term roadmap for agentic AI identity and posture management, ensuring cohesive strategies for reducing risk from agentic AI use
• Maintain and improve our enterprise security posture through high-quality code (Python, Go, or similar) and infrastructure management via IAC
• Act as a technical mentor to junior engineers and a strategic advisor to leadership on the evolving AI landscape

Requirements:

• 7+ years of experience in security engineering or infrastructure security
• 2+ years of experience leading teams in a technical capacity/staff engineering capacity at an enterprise
• Expertise in cloud security (AWS, GCP) and container security (Kubernetes)
• Proven track record of designing and deploying complex security systems at scale
• Strong proficiency in programming languages such as Python, Go, or Java
• This role will be remote, but is not eligible to be hired in San Francisco, CA, Oakland, CA, San Jose, CA, or the surrounding areas
• For this role, you may be required to travel occasionally to participate in project or team in-person meetings
• Experience in building, deploying and reviewing automation for complex security workflows, including use of both AI-driven and traditional automation tools
• Excellent communication skills with the ability to explain complex AI security risks to non-technical stakeholders