Top Tech Jobs & Startup Jobs in NYC, NY

As an Engineering Manager, you'll lead efforts to enhance model performance, manage team projects, and support professional growth in a dynamic environment.

Design and build real-time risk decisioning and tooling to prevent payments fraud. Implement fraud signals at scale, manage dispute and chargeback workflows, monitor metrics (loss, dispute, approval, false positives), lead investigations into emerging fraud patterns, and collaborate cross-functionally with finance, support, legal, data science, and external payment partners.

The Research Engineer will enhance RL training infrastructure, streamline research processes, and collaborate with teams to improve model deployment efficiency.

Join the Web Product team to develop features for Claude.ai, transform user interaction, and enhance AI collaboration. Full-stack work across frontend and backend.

The Product Manager will enhance developer productivity by managing build systems, CI/CD pipelines, and overseeing the developer experience in AI-assisted development, ensuring the efficient code deployment process across engineering teams.

Design and conduct rigorous people research (experiments, longitudinal studies, psychometrics) to measure employee experience, manager effectiveness, and organizational health. Build surveys, analyze data with SQL/Python/R, create visualizations and dashboards, translate findings into recommendations, and partner with People stakeholders to inform people strategy.

The Software Engineer will develop AI-powered cybersecurity products, iterating based on feedback, collaborating with research teams, and engaging with customers to inform product development.

The Scaled Enterprise Account Executive will generate pipeline, manage high-velocity sales cycles, and establish relationships with enterprise accounts, focusing on new customer acquisition and expansion while working closely with technical and business stakeholders.

As a Technical Program Manager, you'll coordinate infrastructure programs, enhance developer productivity, ensure system reliability, and foster cross-team collaboration.

Own vision, strategy, roadmap, and execution for research-driven AI products. Partner with research and engineering to productize models, identify high-potential use cases, synthesize user insights, and ship model capabilities that deliver real-world value.