AI Security Architect

AI Security Architect - GenAI, Agentic Platforms & Secure AI Infrastructure.

Location: Plano, TX (Hybrid)

• The ideal candidate is not simply a traditional security architect with AI awareness, but an architect who has designed and secured AI-native, Agentic, and RAG-based enterprise platforms, understands emerging AI attack patterns, and can translate security principles into enforceable technical controls across the full AI lifecycle.
• This role needs hands-on experience in designing secure AI environments from the ground up, including multi-tenant AI platforms, agentic workflows, Retrieval-Augmented Generation (RAG) systems, AI security gateways, guardrails, model governance, prompt security, memory protection, and secure AI operations.
• Experience in defining and implementing security controls, threat models, and governance frameworks to protect AI systems from emerging threats such as prompt injection, data leakage, model abuse, memory poisoning, tool exploitation, and agent compromise.

Key Responsibilities:

• Design enterprise-grade security architectures for AI, GenAI, LLM, and Agentic AI platforms.
• Build secure AI environments for: LLM applications, multi-agent systems, Autonomous AI workflows, Agentic RAG architectures, Vector databases, and model serving platforms. Implement secure AI gateways and AI orchestration frameworks.
• AI Threat Modeling: Develop threat models covering the following threats: Prompt injection, Jailbreaking, Data exfiltration, Model theft, Agent compromise, Memory poisoning, Cross-tenant attacks, Insider threats, and AI-generated malicious content.
• Knowledge of AI OWASP top 10 threats and mitigation strategies and hands-on experience with MITRE ATLAS.
• Design architectures that secure a multi-tenant AI environment: Tenant isolation, Data Protection (encryption and secrets management, secure token handling), AI Access Control (RBAC, ABAC, Context-aware, zero-trust)
• RAG Security Architecture: Data Leakage prevention, Vector database security (Namespace isolation, Tenant-specific embeddings), Retrieval Governance.
• AI Gateway Security Architecture and Agent Security: Incoming prompt inspection and protection, outgoing response data protection and compliance policies enforcement.
• AI Guardrails Architecture: Input Guardrails (prompt sanitization, classification, and injection detection), Retrieval Guardrails (access verification, data sensitivity checks), and Output Guardrails (data leakage, hallucination check, regulatory and compliance check).
• Define AI security governance - Establish AI security standards, conduct architecture reviews, define security patterns and reusable controls.
• MCP & API security experience is a plus.

Experience:

• 5+ years designing cloud-native security solutions (preferably Azure).
• 3+ years securing AI/ML platforms.
• Experience with LLM security and hands-on experience with MITRE ATLAS
• Experience with agentic AI architectures.
• Experience with AI governance and risk management.
• Hands-on experience in securing LLM-based deployments/applications/servers and MCP-based ecosystems