Jobs at PlayOn Sports

As a Senior Software Engineer, you will create human-in-the-loop and fan-in-the-loop interfaces for AI-driven sports statistics, collaborating with teams to integrate AI models and build dynamic fan experiences across platforms.

Provide phone and email support to MaxPreps users, troubleshoot issues, enter and import high school sports rosters, schedules, and scores accurately, and use MaxPreps live-scoring tools to cover games while minimizing customer effort and improving resolution times.

Produce AI-assisted, data-driven sports video and audio content at scale. Build repeatable workflows and templates, convert sports data into scripts/storyboards, support studio and podcast-to-video production, evaluate AI tools, and maintain editorial quality and brand standards.

Manage post-sale relationships for schools using the GoFan platform to drive adoption, retention, renewals and upsells. Act as customer advocate, provide product guidance, identify churn risk, deliver strategic engagement, and manage multiple accounts to ensure recurring value realization and growth.

Lead engagement and retention for NFHS Network across web, mobile, and CTV. Own roadmap, run experiments, build data-backed business cases, partner with engineering, design, growth and marketing to drive subscriber retention, engagement, and product adoption.

Build and own backend services and APIs that deliver AI-powered, data-driven features. Model and expose sports data for applications and LLMs, optimize Postgres workloads, integrate LLMs with Snowflake/Postgres/internal APIs, and establish evaluation and observability practices for production AI features.

The Staff Software Engineer will lead technical initiatives for subscription growth, oversee experiment cycles, and mentor engineers to improve velocity and quality in product output.

Seeking a Senior Site Reliability Engineer to enhance system reliability, performance, and scalability. Focus on automation, observability, and improving CI/CD practices while collaborating with engineering teams for better incident response and metrics improvement.

Embed on the Video product team to build reusable data models, transformation layers, and pipelines (Snowflake, dbt/SQLMesh). Deliver production-ready data products (APIs, dashboards), instrumentation, experimentation infrastructure, and predictive/causal models to inform product, retention, pricing, and growth decisions.