AI Safety & Responsible AI Lead

AI Safety & Responsible AI Lead

Jersey City, New Jersey, United States (Onsite)

Responsible AI / AI Governance / Model Risk / Ethical A

ILeve

lGovernance Lead / Senior Manager or Director-level Specialis

tTarget / alternate title

sResponsible AI Lead; AI Governance Lead; AI Risk Lead; Model Governance Lead; AI Ethics Lead; AI Policy Lead; AI Safety Lea

dCore keyword

sResponsible AI, AI governance, AI safety, model risk, model governance, AI ethics, fairness, bias, explainability, transparency, hallucination, guardrails, AI risk taxonomy, controls, AIRP, citizen development, Copilot Studio, Power Platfor

mRecruiter red flag

sPolicy-only profile with no production governance; lacks LLM risk understanding; cannot translate principles into controls, workflows, evidence, intake processes, or citizen-development guardrails

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Role purpo**

seDefine and operationalize Responsible AI practices across the AI lifecycle for AIRP and enterprise citizen-development initiatives. The role ensures AI systems are safe, fair, explainable, transparent, compliant, monitored, and aligned with enterprise values, model risk, legal, compliance, data governance, cybersecurity, and audit expectation

s.Client-specific emphas

• isThe organization is aiming to democratize AI responsibly; this role must support enterprise AI plus citizen development through Microsoft Power Platform, Copilot Studio, Power Apps, Power Automate, and Power B
• I.Governance must be practical enough to support business AI use cases while satisfying banking, model risk, security, privacy, and audit control
• s.The candidate should be able to govern high-risk workflows such as KYC, credit underwriting, financial crime, and sanctions screenin

g.Primary ownersh

• ipResponsible AI policy, control framework, risk taxonomy, governance workflows, and production-readiness criteria for AIRP and citizen AI use case
• s.AI risk assessments, impact assessments, safety evaluations, model-risk alignment, and post-production monitoring standard
• s.Cross-functional alignment across engineering, product, legal, compliance, model risk, audit, cybersecurity, data governance, and citizen-development enablement team

s.Key responsibiliti

• esDefine Responsible AI standards, policies, procedures, risk-classification methods, and operating models for AI and GenAI initiative
• s.Establish governance processes for use-case intake, risk assessment, model review, approval workflows, deployment readiness, ongoing monitoring, and issue escalatio
• n.Develop safety and evaluation frameworks covering fairness, bias, explainability, transparency, robustness, privacy, hallucination, harmful outputs, human oversight, and overrelianc
• e.Define guardrail requirements for LLMs, RAG systems, agentic workflows, high-risk banking applications, and citizen-development solution
• s.Partner with model risk, legal, compliance, data governance, cybersecurity, audit, product, engineering, and business teams to align AI controls with enterprise expectation
• s.Lead AI impact assessments, risk reviews, control assessments, readiness reviews, remediation planning, and AI incident escalation processe
• s.Establish metrics and monitoring for bias indicators, safety violations, explainability gaps, harmful outputs, hallucination trends, user feedback, and behavior drif
• t.Create governance playbooks and reusable control evidence for AIRP use cases and Power Platform / Copilot Studio citizen-development workflow

s.Must-have candidate profi

• leDeep understanding of Responsible AI, AI ethics, model governance, model risk, explainability, fairness, privacy, safety, and enterprise risk managemen
• t.Experience implementing AI governance or Responsible AI controls in production or enterprise environment
• s.Understanding of LLM-specific risks such as hallucination, bias, toxicity, prompt injection, data leakage, overreliance, unsafe automation, and human oversight gap
• s.Ability to translate policy and regulatory expectations into practical product, engineering, operating, and audit control
• s.Experience working with cross-functional risk, compliance, legal, security, data, audit, product, and engineering stakeholder
• s.Ability to define controls that scale across centralized AI platforms and distributed citizen-development adoptio

n.Preferred experien

• ceExperience in banking, insurance, fintech, consulting, regulatory risk, model risk manageme…