AI Security Architect

Qualtrics Qualtrics · Seattle · Seattle, WA · Security Engineering & Architecture

The AI Security Architect role at Qualtrics focuses on designing and implementing security frameworks for AI systems to protect against threats like adversarial manipulation, model theft, and prompt injection. This involves leading research, evaluation, and implementation of AI security technologies, conducting security reviews of AI products and agentic systems, and developing security standards and reference architectures. The role requires extensive experience in AI/ML security, cybersecurity architecture, and a strong understanding of adversarial machine learning and secure MLOps.

What you'd actually do

  1. Lead research, evaluation, and implementation of next-generation security technologies and methodologies — adversarial defense, model security, secure MLOps pipelines — that support our AI solutions.
  2. Perform security reviews of AI products and proposed designs, including architectures built on Model Context Protocol (MCP) and agentic AI systems, identifying risks such as tool-use abuse, unauthorized action-taking, and insecure agent-to-agent or agent to-tool communication.
  3. Author AI-related technical security standards, guardrails, and reference architectures that give product and engineering teams a secure, repeatable blueprint for building and deploying AI systems.
  4. Develop a comprehensive AI security strategy that aligns with the organization’s risk profile and business objectives.
  5. Oversee execution of large-scale AI security initiatives, ensuring on-time, on-budget delivery while proactively addressing risks and fostering adaptability within teams.

Skills

Required

  • 5+ years of experience in AI/ML security, cybersecurity architecture, or a related field
  • Proven history of designing secure architectures for AI systems
  • Ability to lead strategic initiatives to strengthen security posture
  • Strong understanding of AI/ML security adversarial machine learning, model security, threat modeling, secure MLOps
  • Familiarity with encryption and secure system design
  • Proven experience leading large scale AI security initiatives
  • Ability to translate AI security challenges into actionable solutions that integrate with business objectives and risk management frameworks
  • Excellent communication abilities to engage effectively with both technical and non-technical stakeholders

Nice to have

  • Experience with Model Context Protocol (MCP)
  • Familiarity with agentic AI systems
  • Experience with tool-use abuse mitigation
  • Experience with insecure agent-to-agent or agent to-tool communication mitigation

What the JD emphasized

  • AI/ML security
  • cybersecurity architecture
  • AI systems
  • security architecture
  • AI security
  • adversarial machine learning
  • model security
  • threat modeling
  • secure MLOps

Other signals

  • AI security architecture
  • adversarial robustness testing
  • model hardening
  • secure MLOps
  • agentic AI systems
  • tool-use abuse
  • guardrails