AI Security Engineer

AI/ML Security Architecture

Design and implement security controls for AI/ML systems across development, training, and production.

Secure LLM integrations, RAG pipelines, and AI APIs.

Conduct threat modeling for AI systems and data pipelines.

Define secure-by-design patterns for AI-powered features.

AI Threat Detection & Mitigation

Identify and mitigate AI-specific threats: prompt injection and jailbreak techniques, model poisoning and data contamination, adversarial attacks, training data leakage, insecure model serialization, excessive permissions in AI agents.

Develop guardrails, content filters, and output validation mechanisms.

Implement monitoring for anomalous AI behavior.

Secure Development & DevSecOps

Integrate AI security checks into CI/CD pipelines.

Perform security reviews of ML code and AI-related infrastructure.

Secure model registries and artifact storage.

Collaborate with other engineers and platform teams to enforce security standards.

Data Protection & Compliance

Ensure AI systems comply with: GDPR and data privacy regulations, financial industry regulatory requirements, implement controls for sensitive data used in training and inference, perform AI risk assessments aligned with internal risk methodology.

Governance & Policy

Contribute to AI security standards and internal policies.

Define AI risk classification and control frameworks.

Support security reviews for new AI initiatives / tools.