Lead Engineer, Next Generation Quant Pricing Platform - Vice President

**The Opportunity: Can You Build the Industry's Premier Risk Quant Pricing Platform?** Are you interested in building the next-generation risk quant pricing platform that runs on large-scale, high-performance compute grids? Are you driven by the challenge of orchestrating trillions of calculations across a hybrid cloud environment to compute risk P&Ls with extreme speed and precision? Do you want to own the core platform that brings sophisticated front-office pricing models to life at an industrial scale? Citi is seeking a visionary Lead Engineer to architect and build our global Quant Pricing Platform. This is the computational heart of our risk system, where complex quantitative models meet massive-scale infrastructure. You will be responsible for creating a seamless, high-performance ecosystem that spans both in-house and external cloud grids, delivering the computational power our quants need to manage risk effectively. **Your Role and Impact** As the Lead Engineer for the Quant Pricing Platform, you are the master of distributed quantitative computation. You will build the end-to-end system that takes pricing models from front-office quants, deploys them onto a colossal hybrid grid, and orchestrates the massive-scale calculation of risk P&Ls. Your primary mission is to engineer a platform that is incredibly powerful, flexible, and efficient, enabling the firm to run complex scenario-based valuations on demand. Your impact is foundational to the firm's risk management capabilities. You will build the bridge between quantitative research and production-scale execution. The platform you create will directly determine the speed, accuracy, and sophistication of our risk calculations, empowering our business to navigate complex markets with confidence. **Key Responsibilities** + Architect and build a next-generation, hybrid-cloud platform for running quantitative pricing calculations at massive scale. + Design a sophisticated job orchestration and scheduling system that handles dynamic **prioritization** , efficient **task packing** , and resource optimization across the grid. + Engineer a robust, event-driven framework for managing the entire job lifecycle, including handling **notifications** for job completion and managing the flow of result data from the grid. + Develop a comprehensive error-handling and resiliency strategy to gracefully manage failures in a large-scale distributed environment. + Pioneer the development of an intelligent **monitoring platform using ML** to perform anomaly detection, predict job failures, and optimize grid performance. + Engineer the secure and efficient data logistics required to move terabytes of market and trade data between on-premise systems and public cloud environments. + Partner closely with front-office quants to onboard, version, and optimize their C++ and Python pricing models for distributed computation. **What We're Looking For** + Professional experience with a proven track record of designing and building applications for **massive-scale, high-performance compute (HPC) grids** . + A degree in a highly technical field such as **Computer Science** or **Quantitative Finance** . + Deep domain knowledge in **Capital Markets** , financial **derivatives** , and a strong understanding of financial regulations like **FRTB** . + Expert-level experience with job scheduling, resource management, and workload optimization techniques ( **task packing, prioritization** ) on large-scale grids. + Deep expertise in building event-driven architectures and handling asynchronous **notifications** and **replies** from distributed systems. + Proven experience designing and building intelligent monitoring tools, ideally leveraging **ML for anomaly detection** and performance tuning. + Expert-level experience managing workloads in a **hybrid cloud environment** , with deep knowledge of at least one major public cloud (AWS, GCP) and on-premise grid technologies. + Deep expertise in containerization, orchestration, and scheduling technologies ( **Docker, Kubernetes** ). + Strong programming skills in languages common to high-performance and quantitative computing, such as **C++** and **Python** . + Proven ability to debug complex pricing and model-related issues by partnering directly with **quantitative analysts** . + Prior experience in a similar role within the financial industry, specifically working on **quantitative pricing platforms** , large-scale risk calculations, or XVA grids. **Education:** + Bachelor's degree/University degree or equivalent experience + Master's degree preferred ------------------------------------------------------ **Job Family Group:** Technology ------------------------------------------------------ **Job Family:** Applications Development ------------------------------------------------------ **Time Type:** Full time ------------------------------------------------------ **Most Relevant Skills** Please see the requirements listed above. ------------------------------------------------------ **Other Relevant Skills** For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ _Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law._ _If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review_ _Accessibility at Citi (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi's_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal opportunity and affirmative action employer. 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