Low-Latency Software Engineer

• Design, build, and optimize greenfield, high-performance distributed trading systems in C++, with a strong focus on latency, scalability, and reliability
• Partner closely with quant researchers and trading teams to translate strategies into production systems and contribute to the overall architecture

• 5+ years of experience in low-latency / high-performance C++ development
• Strong expertise in modern C++ (C++17/20/23) and systems programming
• Experience with multithreading, concurrency, and real-time systems
• Solid understanding of Linux systems and low-level performance optimization

Nice to have:

• Experience in electronic trading systems (market data, execution, or connectivity)
• Understanding of market microstructure
• Knowledge of networking (TCP/UDP) and system-level performance tuning
• Exposure to hardware acceleration (e.g. FPGA)
• Experience with Python for tooling or prototyping

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors., This platform sits at the heart of QRT’s execution capabilities and is designed for ultra-low-latency, high-frequency trading. You will work on systems where performance is critical, contributing directly to how strategies are executed in live markets.

You will collaborate closely with quant researchers and traders to turn models into efficient, production-grade systems, while shaping the architecture and performance of the platform using modern C++ (C++23).