AI Safety & Responsible AI Lead

Title: AI Safety & Responsible AI Lead

Location: Jersey City NJ(Hybrid)

Type: Contract

Primary ownership

• Responsible AI policy control framework risk taxonomy governance workflows and production-readiness criteria.
• AI risk assessments impact assessments safety evaluations and post-production monitoring standards.
• Cross-functional alignment across engineering product legal compliance model risk audit cybersecurity and data governance.

Key responsibilities

• Define Responsible AI standards policies procedures risk-classification methods and operating models for AI and GenAI initiatives.
• Establish governance processes for use-case intake risk assessment model review approval workflows deployment readiness and ongoing monitoring.
• Develop safety and evaluation frameworks covering fairness bias explainability transparency robustness privacy hallucination harmful outputs and human oversight.
• Define guardrail requirements for LLMs RAG systems agentic workflows and high-risk AI applications.
• Partner with model risk legal compliance data governance cybersecurity and audit teams to align AI controls with enterprise expectations.
• Lead AI impact assessments risk reviews control assessments readiness reviews and remediation planning.
• Establish metrics and monitoring for bias indicators safety violations explainability gaps harmful outputs user feedback and behavior drift.

Must-have candidate profile

• Deep understanding of Responsible AI AI ethics model governance model risk explainability fairness privacy safety and enterprise risk management.
• Experience implementing AI governance or Responsible AI controls in production or enterprise environments.
• Understanding of LLM-specific risks such as hallucination bias toxicity prompt injection data leakage overreliance and unsafe automation.
• Ability to translate policy and regulatory expectations into practical product and engineering controls.
• Preferred experience
• Experience in banking insurance fintech consulting regulatory risk model risk management technology governance or data governance.
• Experience building AI risk taxonomies control libraries governance operating models or Responsible AI playbooks.
• Familiarity with global AI governance frameworks model validation practices privacy regulation and audit expectations.