GenAI Governance & Security Specialist

Role Overview: Define and operationalize the security posture and governance framework for all GenAI initiatives. Act as the primary liaison between AI engineering and legal/compliance teams. Key Responsibilities Guardrail Architecture: Design and implement systemic safeguards (e.g., NeMo Guardrails, Llama Guard) to prevent prompt injection, jailbreaks, and PII leakage. Compliance Strategy: Align AI deployments with internal data privacy policies and emerging global regulations (e.g., EU AI Act, GDPR). Risk Assessment: Lead red-teaming exercises and vulnerability assessments on enterprise LLMs and RAG systems. Monitoring Systems: Establish comprehensive observability dashboards to track hallucination rates, toxicity, and bias in production models. Required Skills & Qualifications Tech Stack: Security testing tools, SIEM integrations, Python for automation, LLM observability platforms (e.g., LangSmith, Arize). GenAI Skills: Deep knowledge of LLM vulnerabilities (OWASP Top 10 for LLMs), guardrail frameworks, and data sanitization techniques. Soft Skills: Risk mitigation mindset, strong authoritative communication, ability to balance innovation with compliance. Qualifications: Bachelors/Masters in Cybersecurity, CS, or IT; 47 years in InfoSec, Data Governance, or AI Ethics roles. Role Overview: Define and operationalize the security posture and governance framework for all GenAI initiatives. Act as the primary liaison between AI engineering and legal/compliance teams. Key Responsibilities Guardrail Architecture: Design and implement systemic safeguards (e.g., NeMo Guardrails, Llama Guard) to prevent prompt injection, jailbreaks, and PII leakage. Compliance Strategy: Align AI deployments with internal data privacy policies and emerging global regulations (e.g., EU AI Act, GDPR). Risk Assessment: Lead red-teaming exercises and vulnerability assessments on enterprise LLMs and RAG systems. Monitoring Systems: Establish comprehensive observability dashboards to track hallucination rates, toxicity, and bias in production models. Required Skills & Qualifications Tech Stack: Security testing tools, SIEM integrations, Python for automation, LLM observability platforms (e.g., LangSmith, Arize). GenAI Skills: Deep knowledge of LLM vulnerabilities (OWASP Top 10 for LLMs), guardrail frameworks, and data sanitization techniques. Soft Skills: Risk mitigation mindset, strong authoritative communication, ability to balance innovation with compliance. Qualifications: Bachelors/Masters in Cybersecurity, CS, or IT; 47 years in InfoSec, Data Governance, or AI Ethics roles.