Top AI Jobs in NYC, NY

Lead product strategy and corporate development for AI initiatives at Datadog. Define AI product direction, evaluate market opportunities, partnerships, and M&A, collaborate with cross-functional teams, and support go-to-market and roadmap decisions to accelerate AI capabilities across the platform.

The US Product Lead is responsible for the AI product roadmap, leading a team, driving outcomes, managing budgets, and coordinating cross-functional collaborations to enhance commercial performance through AI-driven solutions.

Lead design and implementation of AI and blockchain-enabled integration and platform architectures. Analyze requirements, develop technical designs, direct large projects, validate outcomes with clients, coach diverse teams, drive cloud strategy (Azure), perform feasibility studies and business process modeling to optimize enterprise technology infrastructure.

Lead technology vision and strategy for tax innovation, focusing on AI, LLMs, cloud, and data-driven platforms. Sponsor and shape major cloud and AI initiatives, build and mentor engineering teams, align technology with business objectives, and ensure governance, risk, and compliance while driving measurable business impact.

Lead the Scheduling product roadmap, shipping mobile calendar and AI-native scheduling features. Balance platform reliability and new capabilities, partner with Engineering/Design/GTM, and drive metrics across booking volume, calendar utilization, and AI engagement to increase GMV and provider retention.

Lead design, launch, and lifecycle management of Pluralsight solutions (AI, Cloud, Security). Define expert POV, build curricula, labs, assessments, and blended learning programs. Own roadmap, metrics, GTM partnership with Sales and Marketing, and continuous iteration using data and SME collaboration to drive enterprise customer outcomes.

Lead market strategy for AI across the platform: define positioning, messaging, and commercialization; drive GTM and launch readiness; provide market and competitive intelligence; influence product strategy and investment decisions; partner cross-functionally to drive adoption, measurement, and long-term customer value for AI-powered capabilities.

Lead and grow an AI Platform Enablement team to build a governed internal AI development environment. Define platform strategy, partner with security and infrastructure, drive adoption via enablement programs, and establish metrics for usage, onboarding, and control effectiveness. Act as an executive-facing leader delivering secure, scalable platforms and change management.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Lead design and deployment of AI solutions, manage end-to-end project delivery, engage clients to define needs, guide teams through complex challenges, innovate processes to improve operations, analyze data trends to inform strategy, and mentor staff while ensuring compliance with model risk management and firm standards.

As a Senior AI/ML Engineer, you will manage the AI/ML lifecycle, develop predictive models, conduct anomaly detection, and integrate AI capabilities into the Confido platform.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

Lead design and implementation of advanced quantitative models and scalable analytics for liquidity, funding, and capital. Develop end-to-end analytics solutions and automation, extract insights from large financial datasets, and partner with Markets Treasury, technology teams, and senior stakeholders to influence strategy and optimize financial resource allocation.

Lead end-to-end execution and governance of AI pilots across the CMO organization. Coordinate onboarding, approvals, and tracking of LOB POCs to avoid duplication; manage the Marketing AI Sandbox; scout external AI solutions and partnerships; and communicate program status to stakeholders while measuring program success and alignment with enterprise priorities.

Lead execution of a firmwide data product approach: define, develop, register, and govern reusable data products. Coordinate with business and CDAO teams, set KPIs/OKRs, produce strategic reports, advise data leaders, and drive adoption of best practices to enable analytics and AI use across the firm.

The Director of AI/Agentic Experience Strategy leads AI-driven customer lifecycle strategies, facilitates AI experience design, and collaborates across teams to enhance consumer interactions in financial services.

The Director of AI Search leads New York Life's AI Search strategy, overseeing AI acquisition strategies and driving AI innovation in marketing experiences. The role requires collaboration across functions to optimize content for AI discoverability and define future-state AI experiences while maintaining compliance and stakeholder alignment.

The Director will strategize and govern AI experiences for field personas, develop frameworks, conduct hands-on AI concept experimentation, and ensure alignment across stakeholders.

Design and deliver AI/ML solutions for Business Banking: build NLP/LLM models, embed AI checks into campaign workflows, integrate data pipelines, automate quality metrics, and partner with cross-functional teams to operationalize and measure AI capabilities for marketing and campaign validation.

Build, tune, and QA conversational AI agents on the Regal platform: design prompts and flows, tune STT/LLM/TTS settings, create custom functions, test agents, codify best practices, and provide product feedback and sales demos.

Lead end-to-end strategy and execution to integrate Google generative AI products across Capital One, drive rapid experimentation, partner with Google product leadership, build quantifiable value cases, balance user experience with enterprise controls, and lead cross-functional teams to scale AI-driven productivity and automation.

Lead design, build, and deploy production-scale generative AI and agentic systems: foundation model training, LLM inference, vector search, guardrails, evaluation, observability, and performance optimization across cloud infrastructure.

Summer Analyst in Data & AI will design and build end-to-end data, analytics, and ML/AI solutions using cloud and modern tooling. Responsibilities include developing models and pipelines, running experiments tied to business KPIs, supporting data governance and compliance, creating dashboards, and collaborating in agile teams while receiving mentorship and training.

Lead end-to-end modeling lifecycle: define objectives, build and deploy neural models and inference pipelines, architect scalable agentic and generative AI solutions, ensure model governance and Responsible AI compliance, present findings to senior stakeholders, maintain vendor relationships, stay current with research, and mentor junior team members.

Lead design and delivery of full‑stack, cloud‑native AI and GenAI solutions; define AI strategies; architect secure, scalable platforms; mentor engineering teams; run pilots, integrate successful technologies, and partner across cloud, security, data, and business stakeholders to improve developer experience and drive enterprise adoption.