Top AI Ethics Jobs in NYC, NY

Senior AI leader responsible for defining enterprise AI strategy, prioritizing high‑value use cases across underwriting, pricing, claims and operations, building an AI organization, partnering with technology/data/risk teams, ensuring regulatory compliance, and driving adoption and measurable business outcomes.

Lead global internal audit coverage for data governance, AI risk management, and infrastructure. Define and execute audit strategy, manage and develop a high-performing audit team, engage senior stakeholders, produce audit findings and reports, and drive adoption of data analytics and automation in audit testing to improve assurance efficiency and compliance with evolving regulations.

Lead design and delivery of a centralized AI control platform to operationalize governance, explainability, monitoring, approvals, and auditability across the AI lifecycle. Partner with risk, legal, compliance, privacy, and audit to meet regulatory expectations, drive adoption, set metrics for control effectiveness, and report AI control maturity to senior management.

The Research Scientist will design evaluation measures for AI systems, collaborate with agencies, and publish research on AI risks.

Build and grow a Formal Methods team to develop practical tooling that verifies and validates agent-generated code. Combine deep formal-methods research (proof assistants, theorem provers, static analysis, refinement types, program logics) with strong software engineering to create tools used across the firm.

As a Technical Product Intern, you'll prototype user safety features, conduct competitive analysis, and translate compliance frameworks into product logic, focused on real-time AI enforcement.

The AI Workforce Enablement Lead promotes AI adoption within an organization by developing training materials, facilitating hands-on learning, and supporting communities of practice. The role involves gathering feedback and tracking metrics to enhance programs while ensuring compliant AI use.

Lead AI safety role developing adversarial prompt strategies, owning end-to-end projects, mentoring junior analysts, managing multilingual abuse datasets, researching circumvention tactics, and partnering with engineering, product, and policy teams to secure generative AI models.

Lead AI compliance testing and governance for enterprise AI use cases (including agentic AI and LLMs). Manage internal AI testing tool, execute quarterly risk-based credible challenge and control assessments, translate consumer compliance regulations into AI testing procedures, and partner with cross-functional stakeholders to escalate and remediate risks.

Lead design and ownership of end-to-end quality systems for Snorkel's Data-as-a-Service. Establish standards, metrics, governance, and automation to measure and scale contributor, datapoint, and dataset quality. Partner cross-functionally to operationalize quality, then build and grow the Quality team while representing Snorkel externally.