Proprietary trading firm with low-latency derivatives trading infrastructure
Geneva Trading operates a low-latency trading platform for listed derivatives, built on Python, C++, kdb+, and FPGA acceleration. The engineering-heavy hiring mix (10 engineers across 15 active roles) focused on mid-level and director positions points to infrastructure scaling — the pain-point list (latency spikes, exchange connectivity, post-trade inefficiency, hardware issues) shows they're optimizing both the data pipeline and risk framework as trading volume grows.
Geneva Trading is a proprietary trading firm founded in 1999, based in Chicago. They trade listed derivatives using in-house technology and diversified strategies, managing significant capital with a 20-year track record. The company operates a custom trading stack combining Python, C++, and kdb+ for data processing, FPGA hardware for sub-millisecond execution, and monitoring tools (Splunk, Prometheus, Grafana, Zabbix) across Linux (Red Hat, CentOS, Ubuntu) and Windows infrastructure. Current focus spans backend services, backtesting frameworks, risk monitoring, and reducing latency in high-frequency execution.
Python, C++, kdb+, NumPy, Pandas, MATLAB for algorithmic work; FPGA for low-latency execution; Splunk, Prometheus, Grafana, Zabbix for monitoring; Linux (Red Hat, CentOS, Ubuntu) and Windows 10 infrastructure.
Chicago, Illinois. They are hiring in the United States and United Kingdom.
Geneva Trading's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.