Top Tech Jobs & Startup Jobs in NYC, NY

Leads a cluster of media buyers managing programmatic campaigns for gaming, sports betting, and performance-led brands. Owns campaign architecture, bidding, supply strategy, budget pacing, KPI performance, optimization, attribution, reporting, and client communication. Coaches traders, manages escalations, conducts training, and establishes standardized trading playbooks and processes across global clusters.

Develops positioning, messaging, go-to-market plans, launches, sales enablement, customer insights, adoption communications, and thought leadership for Genius Sports’ advertising technology portfolio. Partners cross-functionally with Product, Marketing, Commercial, Revenue, Data, and Partnerships teams to simplify complex adtech products, support sales, improve adoption, and demonstrate commercial impact.

Leads end-to-end customer implementations, deployments, go-lives, stabilization, seasonal readiness, and ongoing operational delivery. Coordinates cross-functional internal, customer, and external teams; manages plans, budgets, risks, dependencies, issues, governance, and change requests. Serves as the primary delivery lead, resolves customer-impacting operational issues, facilitates executive reporting, maintains documentation, and drives continuous improvement, scalability, and operational readiness across the customer lifecycle.

Lead critical infrastructure platform initiatives enabling engineering teams to build, deploy, and operate products consistently. Responsibilities include developing multi-account and multi-region Kubernetes clusters, MLOps capabilities, standardized deployment systems, and company-wide authentication. The role also involves automating engineering workflows, improving developer experience, prioritizing shared platform initiatives with stakeholders, driving platform adoption, and mentoring team members.

Design, build, and operate distributed, real-time advertising and fan-engagement systems across the full stack. Lead architecture, implement end-to-end features, improve scalability, reliability, testing and release strategies, and mentor engineering teams. Integrate APIs, databases, messaging/streaming, real-time model inference, and on-site hardware while supporting production deployments and operational excellence.