Software Engineer Library Architect Team Leader
Location: New York City, New York, United States
Be one of the first to apply
The Software Engineer Library Architect Team Leader will work in Bloomberg’s Pricing and Risk department and lead a team of software engineers that will be trusted to:
Develop and maintain the software infrastructure for the multi-asset quant library.
Assist with design and architecture of the pricing library and its external APIs, including review of quant code and integration into the overall Bloomberg library. Implement frameworks for continuous integration, regression testing and quality assurance of pricing models, version control of library releases, and overall compliance to the standards established. Establish programming standards, testing procedures, documentation guidelines and best practices for the overall quant group. Lead the integration of the quant code into the target library. Understand Bloomberg’s code base including legacy code and its dependencies with other libraries and applications
You’ll need to have:
At least five years’ software development experience, preferably as a quantitative developer working on a large derivatives model library. Exceptional C++/C++11 skills and awareness of C++14 and C++17 with a strong capacity of abstraction and design. Significant experience in object-oriented (specifically C++) design and implementation of multi-asset class financial libraries for derivatives pricing. Significant prior development experience on multiple Unix/Linux hardware architectures (servers, SMPs, clusters) and Windows desktop platforms.
Experience with automated build and continuous integration and deployment tools such as CMake, Team City, Jenkins, Incredibuild. Strong skills in efficient software implementation, including parallelization. Advanced degree in Software Engineering, Computer Science, Quantitative Finance, Mathematics, or other quantitative disciplines. Strong communication and collaboration skills with the ability to work within a multi-disciplinary team that includes business managers, software engineers, and quants.
We’d love to see:
Understanding of modeling methods used for pricing and risk management of linear and exotic derivatives such as Monte Carlo and PDE.