LLM RAG Security Engineer

Job Title : LLM RAG & Security Engineer

Location : Sunnyvale, CA or Austin, TX

Job Description :

Experienced LLM RAG & Security Engineer who specializes in evaluating LLM applications and Retrieval-Augmented Generation (RAG) systems, with a strong background in Red Team testing to identify security vulnerabilities in LLM RAG applications. The ideal candidate will have hands-on experience with adversarial testing frameworks such as Garak, PyRIT, or Giskard, ensuring the robustness, security, and reliability of AI-driven systems.

Key Responsibilities :

• Develop & Optimize LLM Applications : Design and implement LLM-powered applications using state-of-the-art models, ensuring efficiency and scalability.
• RAG System Development : Build and fine-tune Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual accuracy and retrieval efficiency.
• Red Team Testing & Security Assessments : Conduct adversarial testing to uncover vulnerabilities such as prompt injection, jailbreaks, data leakage, and bias exploitation.
• Testing with Security Tools : Utilize Garak, PyRIT, Giskard, and other adversarial testing frameworks to evaluate LLM security and model robustness.
• Threat Analysis & Risk Mitigation : Identify LLM security risks, propose mitigation strategies, and work closely with engineering teams to implement secure AI solutions.
• Model Fine-tuning & Guardrails : Implement guardrails, prompt filtering, and defensive techniques to enhance the security posture of deployed LLM applications.
• Collaboration with AI & Security Teams : Work alongside ML Engineers and Data Scientists to integrate security best practices into AI pipelines.
• Performance & Compliance Monitoring : Ensure LLM applications meet security, compliance, and ethical AI standards (e.g., GDPR, AI Act).

Required Skills & Experience :

Preferred Qualifications :