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 Key Responsibilities 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' The base compensation range for this role in the posted location is: 104939 to 118000 Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility