Low Latency Software Developer (C++)
Summary
Design, build, and optimize low-latency, high-throughput C++ systems for a trading firm's mission-critical trading and research infrastructure, including historical market data platforms, strategy simulation tools, and monitoring utilities. Core stack: C++, Python, and Linux.
Responsibilities
- Design, develop, and optimize low-latency, high-throughput software systems used in production trading and research environments.
- Build scalable infrastructure to support efficient storage, retrieval, and analysis of historical market data.
- Develop and enhance simulation platforms used for testing and validating trading strategies.
- Create tools that improve system monitoring, performance measurement, and operational efficiency.
- Collaborate closely with traders, researchers, and global engineering teams to solve complex technical problems.
- Participate in architecture discussions and contribute to the continuous improvement of engineering standards.
- Troubleshoot performance bottlenecks and implement solutions that improve reliability and scalability.
- Stay informed about emerging technologies and industry best practices in high-performance computing and software engineering.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.
- Strong software development experience using C++ in performance-critical environments.
- Good working knowledge of Python for automation, tooling, or application development.
- Solid understanding of Linux operating systems and development environments.
- Proven problem-solving skills with the ability to identify, analyze, and resolve technical challenges.
- Experience working within fast-paced technology organizations and managing multiple priorities effectively.
- Strong communication skills and the ability to collaborate with both technical and non-technical stakeholders.
- Exposure to trading systems, market data platforms, simulation environments, distributed systems, or high-performance computing environments would be advantageous.