AI Security Engineer

Responsibilities

• Conduct security assessments for AI, ML, GenAI, and agentic AI use cases and platforms.
• Evaluate AI systems for prompt injection, insecure outputs, data leakage, unsafe tool execution, model misuse, and retrieval poisoning.
• Review integrations involving APIs, plugins, MCP servers, external tools, vector databases, and enterprise data sources.
• Support threat modeling for AI-powered applications and agentic workflows.
• Implement AI runtime security controls, monitoring, policy enforcement, security guardrails, and observability capabilities.
• Help secure AI gateways, inference endpoints, AI service integrations, cloud deployments, and enterprise environments.
• Collaborate with engineering teams on secure development practices and secure use of AI coding assistants and AI-enabled development tools.
• Support AI onboarding, security reviews, risk remediation, compliance evaluations, and security investigations.
• Provide security guidance related to AI governance, risk management, and enterprise AI adoption.

Requirements

• Bachelor's degree in computer science, cybersecurity, engineering, information technology, or a related field.
• Advanced degrees such as a master's degree are preferred.
• At least 5 years of experience in cybersecurity, application security, cloud security, or related engineering roles.
• At least 2 years of experience supporting or securing AI/ML/GenAI applications or platforms.
• Experience with secure software development lifecycle, application security, and cloud-native security practices.
• Experience with AI/ML platforms, APIs, orchestration frameworks, or AI-assisted development environments.
• Familiarity with AWS and Azure cloud platforms.
• Understanding of LLMs, RAG architectures, embeddings, vector databases, and AI agents.
• Knowledge of AI attack vectors including prompt injection, indirect prompt injection, insecure tool access, and model abuse.
• Familiarity with OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF.
• Knowledge of container security, API security, IAM, secrets management, and cloud security fundamentals.
• AI/ML-related and cybersecurity certifications are preferred.