We are seeking a highly experienced software engineer to lead the design and development of next-generation trading systems. This is a hands-on technical leadership role focused on building scalable, resilient, and high-performance trading infrastructure. You'll collaborate across teams, mentor engineers, and drive innovation in a mission-critical environment.
Design, develop, and optimize KDB+ databases and q analytics for high?volume trading and market data
Develop Python-based AI and quantitative models for research, prediction, classification, and signal generation
Apply machine learning techniques to time?series data (feature engineering, model training, evaluation)
Build research and backtesting frameworks integrating AI models with historical data
Translate quantitative and ML research into robust, production-ready systems
Integrate AI models into real-time and batch pipelines
Optimize analytics and model evaluation for performance, stability, and scalability
Collaborate with quants, product owners, and engineering teams on model deployment and monitoring
The Expertise You Have:
Bachelor's degree in Mathematics, Computer Science, Engineering, Information Technology, or equivalent.
10+ years professional experience in quantitative finance or trading systems
Advanced proficiency in KDB+/q, including:
Time?series data modeling
High?performance querying and joins
Real?time and historical analytics
Strong Python skills for:
Quantitative analysis
AI / ML model development
Integration with KDB+ and downstream systems
Experience working with large-scale, high?frequency, or noisy datasets