JOB SUMMARY
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.
Key Responsibilities
• 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.
• Support production systems and participate in on-call rotations, including occasional weekend support.
Required Qualifications
• 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, and real-time and historical analytics.
• Strong Python skills for quantitative analysis, AI / ML model development, and integration with KDB+ and downstream systems.
• Experience working with large-scale, high-frequency, or noisy datasets.
• Solid software engineering practices (Git, testing, modular design).
• Hands-on experience in AWS or other cloud platforms.
• Experience in Linux, shell scripting, and production support.
Preferred Qualifications
• Worked with AI developer assist tools (e.g. GitHub Copilot).
• Experience with CI/CD tools such as GitHub, Maven, Jenkins, Artifactory, and uDeploy.
• Familiarity with object-oriented programming languages such as Java.
• A 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 communicator with quants, traders, and engineers.
Certifications
