Market Risk Dev with Python,C++

Key Responsibilities

• Architect, build, and manage a massive-scale distributed compute grid on public cloud platforms (AWS, Google Cloud Platform) for running financial pricing models.
• Design and implement the orchestration layer responsible for distributing millions of pricing tasks efficiently across hundreds of thousands of CPU/GPU cores.
• Deploy, manage, and version control a diverse library of quantitative pricing models, ensuring they run optimally in a distributed environment.
• Obsessively monitor and optimize the performance, cost, and resource utilization of the cloud grid, driving continuous efficiency improvements.
• Collaborate with quantitative development teams to seamlessly integrate new and updated pricing models into the production grid.
• Engineer the data logistics to ensure that the correct market data, trade data, and model configurations are available for every calculation at runtime.
• Ensure the pricing engine is highly available, resilient, and capable of meeting stringent recovery time objectives.

What We''re Looking For

• 10 years of professional experience with a proven track record of designing, building, and running applications on massive-scale compute grids.
• Expert-level hands-on experience with at least one major public cloud provider (AWS or Google Cloud Platform), including their batch processing, container, and serverless offerings.
• Deep expertise in containerization and orchestration technologies (Docker, Kubernetes).
• Strong programming skills in languages common to high-performance computing such as C++ and Python.
• Prior experience in a similar role within the financial industry (e.g., running large-scale Monte Carlo simulations, VaR calculations, or XVA pricing grids) is highly desirable.
• A degree in Computer Science, Engineering, or a related technical field.
• A strong background in distributed systems, performance tuning, and infrastructure-as-code principles.
• Exceptional problem-solving skills with an ability to diagnose and resolve complex issues in a high-pressure, large-scale environment.
• Excellent communication skills and the ability to work effectively with quantitative research, trading, and risk management teams.