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.