Overview
On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
Skills
Python
LLM security
Retrieval-Augmented Generation (RAG)
Job Details
Job Description:
Key Responsibilities:
- Design and develop LLM-powered applications ensuring performance, scalability, and efficiency.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual relevance.
- Conduct Red Team testing to identify vulnerabilities such as prompt injection, jailbreaks, data leakage, and bias.
- Utilize tools like Garak, PyRIT, Giskard, and other adversarial testing frameworks to evaluate LLM robustness.
- Analyze security threats and propose risk mitigation strategies for LLM-based systems.
- Implement guardrails, prompt filtering, and defensive techniques to secure LLM deployments.
- Collaborate with AI, Security, and Engineering teams to integrate best practices into development pipelines.
- Monitor performance, security compliance, and ensure alignment with GDPR, AI Act, and other ethical standards.
Required Skills & Experience:
- Proven experience in LLM application development and RAG architecture.
- Hands-on expertise in Red Team testing and discovering LLM security vulnerabilities.
- Proficiency in Python and experience with Hugging Face, LangChain, LlamaIndex, or similar frameworks.
- Deep understanding of LLM security risks including prompt injection and data exfiltration.
- Familiarity with cybersecurity principles and AI security guidelines.
- Strong analytical and problem-solving skills with an eye for secure AI development.
- Experience with machine learning model evaluation, monitoring, and compliance tracking.
Preferred Qualifications:
- Prior experience in LLM security research or AI model penetration testing.
- Background in Natural Language Processing (NLP), information retrieval, and AI ethics.
- Familiarity with secure AI deployments in cloud environments.
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