Jobs at Geneva Trading

The Quant Trader will manage trading positions, analyze data for opportunities, enhance trading tools, and collaborate with teams to solve complex problems in a trading environment.

As a Discretionary Trader, you will leverage advanced technology to scale profitable strategies and identify new opportunities, collaborating with a tech team to enhance trading systems.

Design, build, and maintain internal front-end trading tools, dashboards, and supporting APIs. Partner with traders, Risk, and Technology to gather requirements, improve performance, reliability, and scalability, and provide production support for real-time, high-throughput trading systems.

Build and deploy quantitative risk models, pricing libraries, margin replication tools, and real-time monitoring systems for futures markets. Integrate AI and machine learning for predictive risk modeling, anomaly detection, and trading surveillance. Support live trading, investigate incidents, analyze market behavior, and implement systemic fixes. Collaborate with traders and engineering teams, guide risk-tech architecture, and mentor junior staff. Coverage during Asian market hours may include early mornings or overnight shifts.

The Director of AI Engineering will develop AI-driven solutions, enhance trading workflows, oversee LLMs, and lead AI integration efforts.

Lead the OTC Oil Desk, managing a team of traders, developing trading strategies, and ensuring adherence to risk management and regulatory standards.

As an Experienced Discretionary Trader, utilize innovative technology to scale profitable strategies, identify new opportunities, and collaborate with a technology team.

Design and build Qlik Sense dashboards and data load transformations for middle/back-office teams. Develop and maintain backend services supporting the trade lifecycle, ensure accurate data flows, own audit-trail reporting, support production systems, and improve performance, reliability, and observability.

Lead a small data engineering team and own market data platforms from ingestion through delivery. Build and maintain KDB+/Q time-series systems, ensure data correctness, low-latency decoding, replay/recovery, and reliable distribution to downstream consumers. Write production code, review designs, improve observability, and prepare the platform for AI-driven consumers.