Quant Developer / Software Engineer

• Design and develop high-performance, production-quality trading systems in C++.
• Work closely with traders and quantitative researchers to translate trading ideas into production technology.
• Build and optimise systems across market data, pricing, simulation, order routing and execution.
• Develop infrastructure supporting systematic and automated trading strategies.
• Optimise systems for latency, throughput and reliability.
• Take ownership of projects throughout the full engineering lifecycle.
• Contribute to technical architecture and the continued development of the wider trading platform.

• 5-10 years of professional C++ development experience.
• Excellent understanding of computer science fundamentals, including algorithms, data structures, concurrency, memory management and operating systems.
• Experience building performance-critical, real-time or high-throughput systems.
• Strong understanding of multithreading and performance optimisation.
• Experience developing robust production software in a Linux environment.
• Strong problem-solving skills and ability to work closely with technical and business stakeholders.

Nice-To-Have Experience

• Quantitative trading, electronic trading or broader financial markets experience.
• Equities and/or ETFs experience.
• Market data, order routing, execution or exchange connectivity.
• Low-latency or high-frequency trading systems.
• Pricing, research or simulation frameworks.
• Python alongside C++.

Prior financial markets experience is not essential for all opportunities, and strong C++ engineers from other performance-critical environments are encouraged to apply. The underlying requirements place particular emphasis on strong computer science fundamentals, performance-critical C++ and Linux engineering. xrbllit

Radley James is working with leading quantitative trading firms looking to hire experienced C++ Quant Developers and Software Engineers in New York. These opportunities sit within front-office trading and quantitative technology teams, working closely with traders and quantitative researchers to build high-performance systems supporting systematic trading across equities and ETFs.

The roles cover the full trading lifecycle, from market data and research infrastructure through simulation, pricing and execution, with engineers taking significant ownership of systems from initial design through to production.