Senior Software Engineer

Our client is building at the intersection of motorsports, data, AI-native software, and real-world performance. This team supports a nationally competitive motorcycle racing program where technology is not just behind the scenes—it directly influences race-weekend decisions, rider coaching, setup optimization, and competitive strategy.

This is a rare opportunity to build software that moves from codebase to racetrack, where your work will be tested in fast-moving, high-pressure environments and used by engineers, riders, and race teams who need reliable insights when every second matters.

ABOUT THE ROLE

We are looking for a Senior Software Engineer to help lead the next evolution of a race support platform built for telemetry, analytics, and race-day decision-making.

In this role, you’ll design and ship reliable, high-impact software that helps the team ingest sensor data, analyze performance, optimize setups, and turn complex telemetry into clear, actionable insights. You’ll work across architecture, backend systems, user experience, data modeling, AI-assisted engineering workflows, and field reliability.

This role is ideal for an engineer who loves building practical, durable systems, enjoys solving complex data problems, and wants to see their software make a direct impact in a thrilling, real-world environment.

The role is primarily based in Chicago, with in-office collaboration and occasional work-from-home flexibility. Optional travel to one or two race weekends may provide direct exposure to how the platform performs in the field.

RESPONSIBILITIES

In this role, you’ll own the design, development, and delivery of reliable software that powers race-day telemetry, analytics, and decision support. You’ll build systems for sensor data ingestion, high-volume data processing, offline-ready workflows, and responsive user experiences using technologies such as .NET Core, Blazor, Entity Framework Core, PostgreSQL, and Azure. You’ll also help turn complex racing data into actionable insights for engineers and riders, improve platform reliability in real-world race environments, and use AI-native development practices to accelerate delivery while maintaining strong architecture, code quality, and performance.