Trading Systems Software Engineer

Build scalable Python-based trading infrastructure and distributed systems, partnering with quantitative researchers and technologists to improve research capabilities, production performance, and productivity across expanding markets.

What You'll Do:

1. Build and enhance core platforms supporting trading operations.
2. Develop research infrastructure alongside quantitative researchers.
3. Improve the scalability, reliability, and performance of production systems.
4. Work with technologists to evolve distributed systems and engineering capabilities.
5. Process and analyze large datasets to support trading and research initiatives.
6. Develop solutions that increase productivity across the wider trading organization.

Your responsibilities will include:

1. Designing and developing Python software for large-scale distributed systems.
2. Contributing to critical research and production infrastructure.
3. Identifying technical bottlenecks and developing scalable solutions.
4. Collaborating closely with quantitative researchers and fellow engineers.
5. Taking ownership of projects from conception through implementation.
6. Applying strong analytical and problem-solving skills to complex engineering challenges.
7. Supporting systems running in Linux environments.
8. Helping establish infrastructure capable of supporting expansion into new markets.

Why Join Us:

1. Work directly on technology that powers sophisticated trading operations.
2. Partner closely with quantitative researchers and experienced technologists.
3. Build infrastructure where improvements can multiply the productivity of an entire team.
4. Solve challenging problems involving distributed systems, scalability, and large datasets.
5. Have meaningful ownership and influence as the technology platform expands into new markets.

About You:

1. 5+ years of professional software engineering experience with Python.
2. Strong experience building and supporting large distributed systems.
3. Comfortable working extensively within Linux environments.
4. Proven experience handling and working with large datasets.
5. Excellent analytical and problem-solving capabilities.
6. Naturally curious and motivated to understand complex technical challenges.
7. Self-directed, accountable, and comfortable taking ownership of projects.
8. Able to collaborate effectively with quantitative researchers and technical teams.
9. Bachelor's degree in Computer Science, Computer Engineering, or an equivalent qualification.
10. Reliable, consistent, and dependable in your professional commitments.

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