The RoleWe 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.
