Quant Engineer

About the role

Build and maintain high-performance data pipelines, backtesting and simulation infrastructure, and low-latency execution and signal-processing systems. Partner with researchers to implement and productionize models while ensuring data quality, timing, and reproducibility across the research-to-production lifecycle. Requires production-level Python and SQL experience, performance-sensitive engineering skills, and a track record building data, backtesting, or execution infrastructure in a quantitative or similarly numerically intensive environment. Candidates should understand real-world time-series data issues, use modern AI engineering tools effectively, and be comfortable making autonomous decisions while working in person five days a week.