Tatari
Tatari builds a TV advertising platform that combines media buying with measurement and analytics for brands, agencies, and publishers across linear and connected TV. It sells software and managed buying services to plan, buy, and optimize campaigns with digital-like reporting. Founded in 2016 and headquartered in San Francisco, the privately held company lists customers such as Chime, Calm, and Fubo, and has offices in Los Angeles and New York.
Open Positions at Tatari
6 open positions
Tatari is seeking a Staff QA Engineer to lead test automation strategy and implementation for its TV advertising buying and optimization platform. The role combines hands-on Playwright framework development with technical leadership, data validation, and mentoring.
Tatari is hiring a Staff QA Engineer to lead test automation strategy and build scalable quality systems for its TV advertising platform. The role combines hands-on Playwright framework development, cross-stack testing, release-gate ownership, and technical leadership.
Staff QA Engineer responsible for setting Tatari’s test automation direction and building scalable coverage across its TV advertising buying platform. The role combines hands-on Playwright framework development, backend and data validation, release quality leadership, and mentorship.
Join Tatari’s Reporting & Measurement team as a Senior Backend Engineer building and scaling the systems behind an automated, data-driven TV advertising platform. You’ll lead architecture, mentor engineers, work with modern data and LLM systems, and ship high-quality production code.
Join Tatari’s Reporting & Measurement team as a Senior Backend Engineer building and scaling data-intensive systems for programmatic TV advertising. You’ll own backend features, shape architecture, mentor engineers, and help deploy reliable LLM-enabled capabilities.
Join Tatari’s Reporting & Measurement team as a Senior Backend Engineer building scalable data and advertising platform capabilities. You’ll own architecture and feature development while working with distributed systems, modern data infrastructure, and production LLM-based systems.