Top AI Jobs in NYC, NY

As a Lead AI Engineer, you will design, develop, and support AI systems, collaborating with engineering and research teams to deploy scalable solutions that enhance customer interactions and improve banking services.

Responsible for developing and enhancing an AI SDK, ensuring high performance and integration with deployment platforms, while collaborating with cross-functional teams and engaging with the open-source community.

Lead technology solutions development, manage project delivery, foster collaboration, guide teams, mentor leaders, and promote technological advances.

The Applied AI Engineer designs and deploys AI-powered solutions, collaborating with teams to automate workflows and improve efficiency across Alloy.

Design, build, and scale production LLM, retrieval, and agentic AI systems for compliance automation. Implement evidence-grounded, explainable workflows, optimize for latency/cost/reliability, and embed human-in-the-loop guardrails while collaborating cross-functionally.

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.

Lead and deliver audits of financial statements for digital assets, evaluate governance, compliance, and risk management, apply advanced auditing and technical accounting skills, manage and coach teams, communicate findings, validate outcomes with clients, and model professional standards.

Own technical delivery of Moveworks AI Agents for enterprise customers: gather requirements, design and build integrations and automations, tune LLM-based solutions, advise on AI roadmaps, synthesize feedback to product, and create reusable templates to scale implementations.

Lead product vision and execution for an agentic AI platform: prototype and ship autonomous agent capabilities, define platform primitives (orchestration, memory, execution, governance), drive adoption and measurable outcomes, partner with engineering, frontier AI teams, and GTM to scale enterprise deployments.

Work with the Data team to produce ad-hoc analysis from Snowflake, build and validate data models for Tableau and Streamlit, monitor KPIs, and develop reusable AI-enabled workflows in dbt and the CortexAI semantic layer. Responsibilities include prompt engineering, evaluating model outputs, ensuring data accuracy, and translating analytics into business-facing tools and dashboards.

Lead creation and execution of the CX AI program: set roadmap, design AI-driven support workflows, launch and A/B test flows, track performance metrics, and build operational systems (QA, documentation, reporting) to automate and improve customer experience and business outcomes.

Lead backlog prioritization and delivery coordination for AI platform capabilities (MCP connectors, document ingestion, platform enablement). Translate prototypes into requirements, manage timelines and stakeholder communication, monitor production health, coordinate UAT and governance (RAIC/security), and drive iterative improvements and documentation to support investment teams.

Design, implement, and deploy scalable AI/ML systems. Perform data wrangling, preprocessing, and advanced algorithm development. Collaborate with cross-functional teams to integrate AI solutions, analyze complex datasets for business insights, and support client engagements while continuously improving technical skills.

Support development and implementation of AI governance frameworks, assess governance/risk/controls, gather requirements, document processes, synthesize findings, advise on regulatory compliance, and help design scalable control programs for clients.

Develop and manage AI governance frameworks and risk-control assessments. Translate technical AI concepts for non-technical stakeholders, analyze regulatory and compliance risks, design governance models and controls, interpret data to inform recommendations, build client relationships, collaborate on solutions, and mentor junior team members.

As a Senior Data Scientist, you'll lead AI risk assessments, manage compliance, and evaluate AI system behavior, ensuring safe deployment across banking use cases.

As Product Manager II for AI & Data Security, you'll own the roadmap for AI capabilities, manage security posture, collaborate with engineers and researchers, and engage customers to enhance AI systems security.

The role involves leading AI strategy and implementation, overseeing teams, managing client accounts, and delivering strategic business solutions to enhance client value.

As a Principal Associate Data Scientist at Capital One, you will develop generative AI-based solutions, collaborate with cross-functional teams, and build machine learning models to derive insights from large data sets.

The Lead AI Engineer will develop and deploy AI components, optimize large language models, and improve AI systems performance while collaborating with cross-functional teams.

Lead the development and deployment of AI-powered products with a focus on foundational AI systems, LLM optimization, and team collaboration to enhance user experiences in banking.

As a Lead AI Engineer at Capital One, you will design and support AI software, develop LLM and optimization techniques, and collaborate with cross-functional teams to innovate AI products.

As a Senior Lead AI Engineer, you will design, develop, and optimize AI systems while collaborating with a cross-functional team to implement AI-driven products.

As a Lead AI Engineer, you will design and develop AI components, collaborate across teams, improve performance, and contribute to Capital One's AI vision.

The Senior Lead AI Engineer will design and develop AI-driven products, enhance scalable AI systems, and collaborate with cross-functional teams.