Principal AI Governance & Security Architect

TCC Toyota Motor Credit Corporation Company; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health care and wellness plans

Job summary

Toyota Financial Services in Plano, TX seeks a Principal AI Governance & Security Engineer. This hands-on role sits at the intersection of AI governance, security, and forward deployed engineering.

You will help build the enterprise control plane that lets Toyota deploy AI and agentic systems safely, compliantly, and at scale. A strong software engineering background and deep understanding of AI risk are required.

Qualifications

• 12+ years of software engineering experience and demonstrated experience with AI/ML/Data Governance and associated information-security of AI/ML.
• Designing and implementing enterprise AI or data governance frameworks and operational governance processes in production.
• Translating security, risk, privacy, and compliance requirements into executable controls, measurable tests, and working software.
• Deep understanding of AI/model risk and responsible-AI principles, with working knowledge of SR 11-7, NIST AI RMF, the EU AI Act, and ISO/IEC 42001.
• Practical AI security depth — threat modeling, guardrails, identity and access management, secrets, and least-privilege design.

Responsibilities

• Shape the foundation for Toyota Financial Services' next generation of governed AI and agentic capabilities to ensure safe, auditable, compliant production AI.
• Balance governance rigor with engineering velocity so teams can innovate within guardrails.
• Design and implement enterprise AI governance framework, policies, and procedures across AI lifecycles.

Job description

Toyota Financial Services in Plano, TX seeks a Principal AI Governance & Security Engineer. This hands-on role sits at the intersection of AI governance, security, and forward deployed engineering.

You will help build the enterprise control plane that lets Toyota deploy AI and agentic systems safely, compliantly, and at scale. A strong software engineering background and deep understanding of AI risk are required.