We are working with a rapidly growing quantitative investment firm that is building out its research and trading infrastructure across equities, futures, fixed income, commodities, options and systematic volatility.

The firm is looking for highly technical Quantitative Developers who can work closely with researchers and take ownership of the infrastructure used to research, test and deploy systematic strategies.

This is not a support-oriented quant development role. The ideal candidate will be one of the most technically capable people within the research environment and will be expected to build core components directly.

The role

You will:

1. Design and build high-performance quantitative research infrastructure
2. Develop and improve backtesting frameworks
3. Build tooling used by Quantitative Researchers to develop and validate strategies
4. Work across both C++ and Python
5. Improve the speed, reliability and scalability of research workflows
6. Develop reusable components for simulation, data access, analytics and strategy testing
7. Work closely with researchers on the implementation of systematic trading ideas
8. Help move research from prototype through to production
9. Contribute to broader trading infrastructure as the platform continues to scale
10. Solve technically demanding problems around performance, data, architecture and research productivity

What they are looking for

1. Strong professional experience in quantitative development, trading systems, research infrastructure or systematic investing
2. Excellent Python
3. Strong C++
4. Experience building or materially contributing to backtesting platforms
5. Strong software-engineering fundamentals
6. Experience working with large financial datasets
7. Ability to design robust, reusable research tools rather than one-off scripts
8. Good understanding of systematic trading workflows
9. Ability to work directly with Quantitative Researchers and translate research requirements into production-quality systems

Particularly valuable experience

1. Building backtesting engines from scratch
2. Simulation frameworks
3. Research platforms
4. Market-data infrastructure
5. Strategy implementation
6. Performance optimisation
7. Distributed systems
8. Low-latency or higher-frequency trading environments
9. Numerical libraries / high-performance computation
10. Research-to-production pipelines
11. C++/Python interoperability

Experience across futures, equities, fixed income, commodities, options or systematic volatility is useful, but the firm is primarily focused on technical quality rather than a narrow asset-class background.

The environment

The firm is in a significant build-out phase and is continuing to invest heavily in both research and technology.

Quant Developers sit very close to the investment process and are expected to have genuine ownership. Strong candidates should be comfortable being the technical expert within a research team rather than operating as a purely downstream developer.

The research platform is heavily Python-based, so strong Python is essential , while C++ is particularly valuable for performance-sensitive components and trading infrastructure.

Location

New York City

The firm is substantially expanding its New York presence and can base strong Quant Developers there across multiple investment teams.