AI Security Engineer

AI Security Engineer

Remote

6+ Months

Responsibilities:

·         Responsible for identifying and mitigating security risks in artificial intelligence systems, ensuring the confidentiality, integrity, and availability of AI models and data.

·         Responsible for work cross\-functionally with data scientists, engineers, and cybersecurity teams to design, build, and maintain secure AI systems across their entire lifecycle.

·         AI Threat and Risk Assessment: Identify and assess AI\-specific threats, including adversarial attacks, data poisoning, model inversion, and data leakage.

·         Secure AI Pipeline Development: Implement security best practices throughout the AI/ML development lifecycle from data ingestion and training to deployment and monitoring.

·         Tooling & Automation: Develop and deploy tools for automated threat detection, model monitoring, and vulnerability scanning in AI Workflows.

·         Cross\-functional Collaboration: Partner with software engineers, data scientists, DevOps, legal, and compliance teams to ensure secure and responsible AI development.

·         Monitoring & Incident Response: Establish real\-time monitoring, logging, and incident response procedures for AI systems in production.

·         Compliance & Governance Alignment: Ensure alignment with relevant cybersecurity standards and AI\-related regulations (e.g., ISO/IEC 27001, NIST, and GDPR).

Required Skills:

·         Required 12+ years of professional experience in python, cybersecurity, software engineering, or AI/ML system development

·         Proficiency in Python; experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit\-learn.

·         Solid understanding of cybersecurity fundamentals and secure software development Practices.

·         Experience with cloud platforms (AWS, Azure, or GCP) and securing cloud\-native applications.

·         Familiarity with security tools (e.g., static/dynamic analyzers, monitoring tools, threat modeling platforms).Experience building or securing large\-scale ML Infrastructure.

·         Knowledge of privacy\-preserving ML techniques (e.g., differential privacy, federated learning).Familiarity with AI governance, fairness, or explain ability Frameworks.

·         AI certification is a plus