Job description

Client: Toyota Financial Services Job: AI Security, Engineer Duration: 12 Months Location: Plano , ,TX (Hybrid) Pay : $90-95/hr on w2 We are seeking a forward-thinking AI Security Engineer to help secure our AI/ML systems and infrastructure. This role is ideal for someone with a strong background in cybersecurity and a passion for artificial intelligence. You will be responsible for identifying and mitigating risks in AI models, data pipelines, and AI-powered applications, ensuring the integrity, confidentiality, and availability of our AI systems What you’ll be doing: • Design and implement security controls for AI/ML systems, including model training, inference, and data pipelines. • Identify and mitigate threats such as model inversion, data poisoning, adversarial attacks, and prompt injection. • Collaborate with data scientists, ML engineers, and DevOps teams to integrate security into the AI/ML lifecycle. • Conduct threat modeling and risk assessments for AI systems and algorithms. • Monitor AI systems for anomalous behavior and potential misuse. • Secure APIs and endpoints used for model access and inference. • Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) in AI workflows. • Develop and enforce AI security policies, standards, and best practices. • Stay current with emerging threats and research in AI/ML security. Requirements: What You Bring: • Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Machine Learning, or a related field. • 3+ years of experience in cybersecurity, with at least 1 year focused on AI/ML systems. • Strong understanding of machine learning workflows, model architectures, and data pipelines. • Familiarity with AI-specific threats such as adversarial ML, model extraction, and data leakage. • Experience with Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Knowledge of secure software development practices and DevSecOps principles. Added bonus if you have: • Experience with securing LLMs and generative AI systems. • Familiarity with AI governance, model explainability, and ethical AI principles. • Hands-on experience with tools like IBM Adversarial Robustness Toolbox, Microsoft Counterfit, or similar. • Certifications such as: • Certified AI Security Specialist (CAISS) • GIAC Machine Learning Security Engineer (GMSE) • CISSP, OSCP, or CEH with AI/ML experience

Requirements