Top AI Ethics Jobs in NYC, NY

Lead and evolve the enterprise AI risk and governance framework. Identify and assess emerging AI risks, translate them into governance and controls, run AI approval processes, provide second-line challenge to stakeholders, partner across functions to embed controls, and strengthen monitoring, transparency, and scalable governance for AI initiatives.

Leads independent validation and governance of predictive, generative, and agentic AI models. Develops evaluation frameworks, benchmarks, testing protocols, monitoring, observability, and third-party validation practices. Translates regulatory and model-risk requirements into controls, standards, playbooks, and audit evidence. Presents findings to senior leaders and governance committees, mentors colleagues, and partners with data science, engineering, legal, compliance, cybersecurity, and risk teams.

Lead cross-functional programs to design and automate AI/ML governance for generative and agentic models. Develop program plans, risk mitigation, scalable controls, playbooks, and stakeholder alignment to accelerate model lifecycle delivery while ensuring compliance, quality, and responsible AI practices.

Manage and enable the firm's core AI legal applications: triage attorney inquiries, coordinate vendors and stakeholders, oversee rollouts and integrations, track adoption and value, maintain governance, documentation, and training to drive responsible AI use.

Build and operate Adyen’s enterprise AI governance framework, translating global AI and privacy laws into policies, standards, assessments, and practical workflows. Advise on generative and agentic AI, risk classification, model evaluation, fairness, explainability, red teaming, privacy, and human oversight. Partner cross-functionally with Risk, Security, Product, Compliance, Legal, Engineering, and Data Science; deliver training, monitor regulatory developments, and support audits and inquiries.

Develop and advance Mastercard’s global AI policy positions, narratives, and advocacy strategies. Advise internal executives, business units, government affairs teams, regulators, and standards bodies on AI legislation, regulation, standards, governance, and deployment risks. Translate technical AI concepts and business objectives into policy frameworks, briefs, consultations, and executive materials. Monitor global developments, support thought leadership, engage standards organizations, and coordinate cross-functional responses across legal, regulatory, privacy, cybersecurity, and Services teams.

Lead internal AI adoption by treating AI platforms as products, building training and community programs, mentoring AI Champions, and partnering with business units to rapidly prototype and launch AI POCs while maintaining governance and continuous improvement.

Lead UX research to define and scale evaluation of Notion's AI experiences. Create reusable rubrics and measurement approaches, run longitudinal and feature-specific studies, identify failure modes and recovery behaviors, and operationalize evaluation with product, design, engineering, and data science partners to improve model output quality and end-to-end user experience.

Design and deliver custom AI-driven legal workflows, implement and scale post-sales solutions, define KPIs and success metrics, inform product strategy, partner with Customer Success to demonstrate ROI, and maintain objective, ethics-compliant processes and playbooks for plaintiff law firms.

Lead strategy and architecture for the enterprise knowledge/context layer powering AI: set standards, control models, connector strategy, and federated operating models. Ensure content is AI-ready, permissions-aware, and measurable for retrieval and grounding. Partner with IT, Engineering, Legal, Privacy, and Security to define eligibility, sensitivity, and lifecycle policies and drive adoption across domains.