AI Safety and AI Lead
Listed on 2026-10-17
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IT/Tech
AI Evaluation, AI Engineer (Applied/Software), AI Business & Operations, Information Security & Data Protection
Req : 382100
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us.
We are currently seeking a AI Safety and Responsible AI Lead to join our team in Jersey City, New Jersey (US-NJ), United States (US).
AI Safety & Responsible AI Lead Responsible AI / AI Governance / Model Risk / Ethical AI Role purposeDefine 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 expectations.
Client-specific emphasis- The 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 BI.
- Governance must be practical enough to support business AI use cases while satisfying banking, model risk, security, privacy, and audit controls.
- The candidate should be able to govern high-risk workflows such as KYC, credit underwriting, financial crime, and sanctions screening.
- Responsible AI policy, control framework, risk taxonomy, governance workflows, and production-readiness criteria for AIRP and citizen AI use cases.
- AI risk assessments, impact assessments, safety evaluations, model-risk alignment, and post-production monitoring standards.
- Cross-functional alignment across engineering, product, legal, compliance, model risk, audit, cybersecurity, data governance, and citizen-development enablement teams.
- 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, ongoing monitoring, and issue escalation.
- Develop safety and evaluation frameworks covering fairness, bias, explainability, transparency, robustness, privacy, hallucination, harmful outputs, human oversight, and over reliance.
- Define guardrail requirements for LLMs, RAG systems, agentic workflows, high-risk banking applications, and citizen-development solutions.
- Partner with model risk, legal, compliance, data governance, cybersecurity, audit, product, engineering, and business teams to align AI controls with enterprise expectations.
- Lead AI impact assessments, risk reviews, control assessments, readiness reviews, remediation planning, and AI incident escalation processes.
- Establish metrics and monitoring for bias indicators, safety violations, explainability gaps, harmful outputs, hallucination trends, user feedback, and behavior drift.
- Create governance playbooks and reusable control evidence for AIRP use cases and Power Platform / Copilot Studio citizen-development workflows.
- 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, over reliance, unsafe automation, and human oversight gaps.
- Ability to translate policy and regulatory expectations into practical product, engineering, operating, and audit controls.
- Experience working with cross-functional risk, compliance, legal, security, data, audit, product, and engineering stakeholders.
- Ability to define controls that scale across centralized AI platforms and distributed citizen-development adoption.
- 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, Responsible AI playbooks, or model-risk-aligned review processes.
- Familiarity with Power Platform, Microsoft Copilot Studio, Power Apps, Power Automate, Power BI, global AI governance frameworks, model validation practices, privacy regulation, and audit expectations.
NTT DATA provides a reasonable range of compensation for U.S.
-based positions. The starting pay range for this role will depend on the nature of the role offered and will either be [$155,700 - $259,500], if the role is hired as a temporary…
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