Top Tech Jobs & Startup Jobs in NYC, NY

The Project Manager oversees project coordination and completion, manages schedules and budgets, and communicates with stakeholders.

The Product Marketer will create compelling customer stories, sales collateral, and web content while building relationships with customers and sales teams, managing content production agencies, and communicating technical product benefits.

Lead client engagements across the US market, managing the full commercial lifecycle from consultation to onboarding and ensuring professional execution.

The Android Developer will design and develop mobile applications, optimize performance, and ensure strong UI experiences, requiring extensive Android and Java experience.

Supervising Attorney will lead Prisoners' Rights Project litigation and policy work, maintain an active caseload, direct legislative and administrative advocacy, supervise and develop staff, coordinate with pro bono and internal partners, manage unit operations, and conduct community education and outreach to advance systemic reforms for incarcerated people.

The AI DevOps Engineer will design, deploy, and manage scalable AI infrastructure, focusing on automation, security, and high performance while ensuring compliance within financial services.

Giant Pictures seeks movie enthusiasts interested in digital distribution, film programming, and streaming. Apply to join their talent community for future opportunities.

This role involves requirements elicitation, documentation, coding, support for implementation, and collaboration with teams for high quality deliverables in Warehouse Management System projects.

Lead and build the strategic finance and FP&A function: own the operating model, budgeting/forecasting, capital allocation analyses, GTM and SaaS metric analytics, headcount planning, ERP/finance systems migrations, international consolidations, board reporting, and cross-functional initiatives to inform leadership decisions and support company growth.

Build and operate the end-to-end data layer: ingest and sync EHRs and customer systems, transform messy sources into a normalized patient/provider model, maintain data freshness and query performance, and enable natural-language query interfaces and serving for production AI workloads.