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 machine learning 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 of 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.
Strong software engineering practices including Git, testing, and modular design.
Experience working with AI developer assistance tools (e.g., GitHub Copilot).
Experience with CI/CD tools such as GitHub, Maven, Jenkins, Artifactory, and uDeploy.
Hands-on experience with AWS or other cloud platforms.
Familiarity with object-oriented programming languages such as Java.
Experience with Linux, shell scripting, and production support.
The Skills You Bring
Strong quantitative mindset with practical AI application skills.
Ability to bridge research, machine learning, and production systems.
Comfort working on front-office or research-critical infrastructure.
Clear communication skills with quants, traders, and engineers.
Willingness to support production systems and participate in on-call rotations, including occasional weekend support.