AI Application Security Engineer

Key Responsibilities

• Evaluate AI models and recommend the most secure, scalable, and cost-effective solutions.
• Design and implement security guardrails, policy enforcement, and testing frameworks for AI applications.
• Support AI development pipelines, including Model Context Protocol (MCP) implementations.
• Develop and maintain application security policies for AI-powered applications.
• Build and manage AI policy servers and governance frameworks.
• Perform security assessments for AI/LLM applications and identify potential risks.
• Collaborate with engineering teams to integrate security throughout the AI software development lifecycle.
• Communicate AI security risks, governance, and compliance requirements to both technical and business stakeholders.
• Drive adoption of secure coding practices and AI security standards across the organization.
• Bridge modern AI development practices with enterprise Application Security programs.

Required Skills

• Strong experience in Application Security (AppSec).
• Hands-on experience securing AI/LLM applications.
• Knowledge of Model Context Protocol (MCP) or AI pipeline architectures.
• Experience implementing AI security guardrails and policy enforcement.
• Familiarity with OWASP Top 10, Secure SDLC, and threat modeling.
• Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
• Knowledge of REST APIs, microservices, and modern application architectures.
• Strong scripting/programming skills in Python, Java, or Go.
• Excellent communication and stakeholder management skills.