Join the team as Twilio's next Staff Engineer, AI Security.
\nAs 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.
\nResponsibilities:
\nServe as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.
\nDesign and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.
\nBuild and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.
\nDevelop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.
\nHelp govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.
\nManage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.
\nAuthor company wide AI security standards and implement these security checks across Twilio's stack.
\nImplement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.
\nPartner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.
\nAct as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&D teams
\nQualifications:
\n8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).
\nExpertise 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.
\nHands-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.
\nProficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.
\nStrong communication skills to translate complex AI risks into actionable business logic for stakeholders.
\nDesired:
\nHands-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.
\nExpertise in identity standards including OAuth 2.1 and PKCE.
\nExperience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.
\nProficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.
\nProven 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.
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