Senior Software Engineer, Data

PlayOn is looking for a Senior Software Engineer to develop AI-powered, data-driven services and features for web experiences used by millions of high school sports fans. This role is embedded in a product development team and combines strong backend delivery ownership with hands-on work on the data, APIs, and LLM integrations that power them.

You’ll partner closely with product and engineering teams to shape how our sports data is modeled, defined, and exposed to both applications and LLMs, and build the systems that bring those features to our audiences.

The outcomes you’ll deliver

• Ship AI-powered, data-driven features and experiences grounded in PlayOn’s data
• Build, maintain, and improve APIs and backend services
• Design and evolve data schemas and APIs that make our sports data accessible to both application code and LLM-driven features
• Drive technical decisions for the features you ship, and contribute to performance and operational health across the application
• Establish eval and observability practices for AI features so regressions are caught in CI rather than by users

Develop modern backend services using C# .NET, Python, SQL, AWS, and Snowflake

Build LLM-powered features against PlayOn’s data, connecting models to Postgres, Snowflake, and internal APIs via retrieval, tool use, and semantic search

Model and evolve data schemas so they serve both traditional APIs and AI-driven access patterns

Own features end-to-end: architecture and design, implementation, testing, observability, and operational readiness

Plan and execute backend migrations, platform upgrades, and modernization initiatives with minimal risk

Optimize and monitor PostgreSQL workloads, including query performance, indexing, and database health trends

Define and maintain eval suites for production AI features (retrieval quality, answer accuracy, and regression detection) wired into CI

5+ years of professional software engineering experience, including backend web application development

Experience building production features backed by LLMs, such as RAG, semantic/vector search, or tool use / function calling

Hands-on experience with cloud data warehouses (Snowflake or similar)

Strong expertise in C# .NET, Python, SQL, REST API design, and data modeling

Working knowledge of AWS for deploying and operating backend services

Experience building eval frameworks for AI systems, including golden sets, LLM-as-judge, and regression detection, applied to production AI features and/or agentic dev workflows

Solid PostgreSQL experience, including schema design, query tuning, and modeling data for both transactional and analytical/AI access patterns

Experience with CI/CD pipelines, automated testing, and Git/GitHub workflows

Ability to work effectively in a collaborative, agile, team-oriented environment

Bachelor’s in Computer Science or equivalent experience preferred

You Might Also Have

• Frontend development experience
• Proficiency with load testing, observability, and reliability engineering practices
• Experience working on high-traffic public-facing websites
• Experience with vector databases or vector search
• Experience exposing data and tools to LLMs via function calling, MCP, or agent frameworks
• Knowledge of or interest in sports, sports management, and statistics

Ownership over Participation- You take responsibility for achieving holistic outcomes, prioritize key objectives, and adapt quickly when situations require a different approach. You follow through even against the toughest challenges.

Team over Stars- You are a bridge builder, establishing processes and relationships with teams outside your own. You work to rally around common goals, find win-win solutions, compromise when necessary, and help others succeed.

Growth over Comfort- You are driven by a desire to grow and actively seek opportunities to expand your comfort zone, skills, and confidence. You embrace new challenges with curiosity, accepting discomfort and failure as opportunities to learn. 

Fairness over Popularity- You approach decisions with a scientist’s mindset, challenging your assumptions and remaining objective. You consider long-term impact rather than relying on short-term gains, proactively seek others’ perspectives, and manage emotions in decision-making.