Top AI Ethics Jobs in NYC, NY

Design, configure, and maintain enterprise AI governance platforms and workflows (evidence capture, controls, reporting). Build integrations and automations with enterprise systems, enable metrics and data quality, translate Responsible AI policies into operational controls, coordinate vendors, and deliver training and enablement to drive adoption and audit readiness.

Leads TD Securities’ first-line AI Governance function, overseeing AI use-case intake, risk assessment, approvals, monitoring, issue remediation, controls, and lifecycle oversight. Partners with Front Office, Technology, Risk, Compliance, Legal, Privacy, Cybersecurity, Audit, and enterprise AI stakeholders. Develops governance frameworks, standards, taxonomies, metrics, and reporting while supporting regulatory reviews, audits, and responsible AI adoption across capital markets.

Leads responsible AI adoption across eDiscovery and litigation support, translating strategy into defensible workflows, measurable efficiency, and cost control. Manages AI pilots, governance, workflow redesign, training, vendor relationships, and adoption metrics. Oversees eDiscovery advisors and subject matter experts while advising attorneys, clients, leadership, and technology teams on legal technology, AI governance, data privacy, and complex cross-border matters.

Own the strategy, design, development, and deployment of AI safeguards systems and product experiences across Anthropic’s products and cloud platforms. Define safety-by-design approaches, develop evaluations and risk metrics, prioritize roadmaps, make technical tradeoffs, and collaborate with policy, research, engineering, enforcement, and product stakeholders to mitigate deployment and user risks.

Lead delivery of AI governance programs for financial services clients: build policies, controls, operating models, and KPIs; perform assessments, audits, and model reviews; operationalize monitoring and incident management; support sales, offering development, thought leadership, and people management across multidisciplinary teams.

Own end-to-end AI safety and red-teaming programs for frontier AI labs. Design adversarial testing and jailbreak methodologies, evaluate models across high-severity harm categories and agentic settings, lead expert testing teams, partner with policy stakeholders, synthesize findings into reports, and develop workforce models to improve delivery reliability.

Supports financial services customers in deploying AI risk evaluations and guardrails. Translates laws, regulations, and industry guidance into practical controls; designs, documents, tests, and validates guardrails; partners with product and technology teams on user experience; tracks roadmap objectives and performance; and organizes industry roundtables and customer workshops.

Lead strategy and execution for agentic AI product experiences across the DFIR portfolio. Define roadmaps, ship reliable and governed agentic features, drive adoption and growth, instrument metrics and experiments, run continuous discovery, and collaborate cross-functionally to ensure trustworthy, scalable AI-native products.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Leads the foundation’s responsible AI portfolio, strategy, governance, policy development, model evaluation, vendor assessment, and production deployment. Designs ethical AI solutions using modern machine learning and generative AI technologies, while optimizing performance, cost, scalability, and sustainability. Partners with executives, technical teams, vendors, and nontechnical staff to build AI literacy, communicate complex concepts, manage risks, and promote fairness, transparency, privacy, and responsible innovation across the organization.