Staff Engineer, AI Security

About the Role

As a Staff Engineer, AI Security on the AppSec team, you’ll lead autonomous defense for the AI lifecycle. Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&D to define the MLSecOps roadmap, you’ll ensure a "secure-by-default" future for agentic workflows and resilient AI innovation.

Responsibilities

• Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.
• Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.
• Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.
• Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.
• Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.
• Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.
• Author company wide AI security standards and implement these security checks across Twilio’s stack.
• Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.
• Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.
• Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&D teams.

Required Qualifications

• 8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).
• Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.
• Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.
• Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.
• Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.

Desired Qualifications

• Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.
• Expertise in identity standards including OAuth 2.1 and PKCE.
• Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.
• Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.
• Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.