Market Risk Dev with Python,C++

The Opportunity Can You Build and Command a Cloud Supercomputer Want to run one of the largest highperformance computing grids in the financial industry Are you driven by the challenge of orchestrating trillions of calculations across thousands of cloud cores to price the firms entire trading book in minutes not ours Do you want to build the massivescale valuation engine that powers Citis nextgeneration risk platform Citi is seeking a visionary Cloud HPC Engineer to lead the development and operation of our global pricing grid This is the engine room of our risk system You will be responsible for deploying scaling and optimizing the computational factory that runs our most complex pricing models at an unprecedented scale on public cloud platforms like AWS and GCP Your Role and Impact As the lead for the Pricing Engine you are the master of massivescale computation You will take the sophisticated pricing models developed by our top quants and operationalize them on a colossal grid Your primary mission is to ensure that millions of trades can be revalued against thousands of historical market scenarios with extreme speed efficiency and rocksolid stability Your impact is at the core of our risk valuation capability You will architect the system that answers the most fundamental question in risk What is it worth right now under this scenario The performance and reliability of the platform you build will directly determine the firms ability to manage risk and meet its most critical regulatory obligations, Architect build and manage a massivescale 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 Were Looking For

10 years of professional experience with a proven track record of designing building and running applications on massivescale 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 highperformance 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 problemsolving skills with an ability to diagnose and resolve complex issues in a highpressure largescale environment Excellent communication skills and the ability to work effectively with quantitative research trading and risk management teams