Infrastructure Engineer

Infrastructure Engineer (C++ / Data Infrastructure / Simulation)

Our client is a leading systematic hedge fund at the forefront of quantitative finance, powered by a team of world-class researchers and engineers. As the firm continues to expand its global trading operations, it is investing heavily in building the next generation of its quantitative research and trading infrastructure.

The Infrastructure Engineering team plays a critical role in designing, developing, and optimizing the technology that powers systematic trading strategies. Depending on your strengths and interests, you may contribute as a C++ Trading Engineer, C++ Simulation Engineer, or Data Infrastructure Engineer, working alongside quantitative researchers and traders to build highly scalable, low-latency systems.

Responsibilities

• Design, develop, and optimize high-performance, low-latency trading and research systems using modern C++ and Python.
• Build scalable data processing pipelines to support large-scale financial and market data ingestion.
• Develop tools for backtesting, simulation, model training, and strategy evaluation.
• Collaborate closely with quantitative researchers and traders to deliver robust technical solutions.
• Develop and optimize distributed systems for research and trading workloads.
• Participate in code reviews, testing, documentation, and continuous system improvements.
• Research and implement new technologies to improve infrastructure performance and scalability.

Requirements

• Bachelors, Masters, or PhD in Computer Science or another STEM discipline.
• Minimum 2 years of professional C++ development experience in high-performance or real-time systems.
• Strong knowledge of modern C++ (C++17/20), including template metaprogramming.
• Experience building high-throughput, low-latency applications.
• Strong Linux systems programming skills.
• Working knowledge of Python and scientific libraries such as NumPy and SciPy.
• Excellent analytical and problem-solving abilities.
• Ability to work independently in a fast-paced engineering environment.

Nice to Have

• Experience with distributed systems (Kafka, Redis, HTCondor).
• Experience with market data, exchange connectivity, or financial systems.
• Knowledge of matrix computation libraries (Blaze, OpenBLAS, LAPACK).
• Experience profiling and optimizing Linux systems.
• Familiarity with time-series processing or event-driven architectures.
• Experience integrating C++ and Python using pybind11 or similar technologies.
• Prior exposure to quantitative finance or algorithmic trading.

Whats on Offer

• Competitive base salary with performance-based bonus.
• Opportunity to work alongside world-class quantitative researchers and engineers.
• Ownership of high-impact engineering projects.
• Collaborative, research-driven environment with exposure to cutting-edge technology.
• Comprehensive healthcare and insurance benefits.