Resumen del rol

Staff Engineer, AI Security

Requisitos y responsabilidades

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Details

  • 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
  • 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.
  • 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.
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