Cloud HPC Engineer

Key Responsibilities:

• Architect build and manage a massive scale distributed compute grid on public cloud platforms AWS GCP for running financial pricing models

• Design and implement the orchestration layer responsible for distributing millions of pricing tasks efficiently across hundreds of thousands of CPUGPU 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 are Looking For:

• Experience with a proven track record of designing building and running applications on massive scale compute grids

• Expertlevel Handson experience with at least one major public cloud provider AWS or GCP 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 eg running largescale 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 infrastructureascode principles

• Exceptional problem-solving skills with an ability to diagnose and resolve complex issues in a high pressure largescale environment

• Excellent communication skills and the ability to work effectively with quantitative research trading and risk management teams".