Staff Engineer, AI Security

Twilio Twilio · Enterprise · Ireland · Remote · Security

Staff Engineer, AI Security role focused on building autonomous defense for the AI lifecycle, including multi-agent frameworks, secure gateways, and real-time security gates. The role involves defining the MLSecOps roadmap and ensuring security for agentic workflows.

What you'd actually do

  1. Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.
  2. Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.
  3. Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.
  4. Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.
  5. Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.

Skills

Required

  • security engineering
  • AI security operations (MLSecOps)
  • orchestrating multi-agent systems
  • AWS Strands
  • LangGraph
  • CrewAI
  • runtime isolation
  • PII redaction
  • indirect prompt injection
  • agentic environments
  • AI-specific frameworks
  • MITRE ATLAS
  • MAESTRO
  • OWASP Top 10 for LLMs/Agents/MCP
  • threat modeling
  • direct prompt injection
  • training data poisoning
  • tool poisoning
  • data exfiltration
  • agentic workflows
  • securing AI pipelines
  • data ingestion
  • model training
  • model deployment
  • model monitoring
  • communication skills
  • AI risks
  • actionable business logic

Nice to have

  • modern application security tooling
  • SAST
  • SCA
  • DAST
  • AI specific vulnerabilities
  • identity standards
  • OAuth 2.1
  • PKCE
  • AI Red Teaming
  • adversarial simulations
  • Large Language Models (LLMs)
  • agentic systems
  • Python
  • Go
  • container security
  • workload isolation
  • autonomy
  • drive high impact outcomes
  • ambiguous environments
  • identifying and executing on critical projects
  • predefined roadmaps
  • direct supervision

What the JD emphasized

  • 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.

Other signals

  • AI security
  • multi-agent systems
  • autonomous defense
  • MLSecOps