Lead Engineer, Next Generation Quant Pricing Platform - Vice President

Role overview

Key responsibilities

• Architect and build a hybrid-cloud platform for large-scale quantitative pricing calculations.
• Design job scheduling and orchestration for prioritization, task packing, and grid resource optimization.
• Build event-driven job lifecycle management, including completion notifications and result-data handling.
• Develop failure handling and resiliency for distributed systems.
• Build ML-enabled monitoring for anomaly detection, failure prediction, and grid performance optimization.
• Move market and trade data securely and efficiently between on-premise systems and public cloud environments.
• Work with front-office quants to onboard, version, and optimize C++ and Python models for distributed computation.

What the role requires

• Professional experience building applications for massive-scale, high-performance compute grids.
• Deep experience with job scheduling, resource management, workload optimization, event-driven architectures, and distributed systems.
• Hybrid-cloud workload expertise, a major public cloud such as AWS or GCP, and on-premise grid technologies.
• Expertise in containerization, orchestration, and scheduling technologies such as Docker and Kubernetes.
• Strong C++ and Python programming skills; ability to debug pricing and model issues with quantitative analysts.
• Prior financial-industry experience with quantitative pricing platforms, large-scale risk calculations, or XVA grids.

Domain and education

• Technical degree such as Computer Science or Quantitative Finance; the description also states a bachelor's degree or equivalent experience.
• Deep capital-markets and derivatives knowledge and understanding of financial regulations such as FRTB.
• The provided source description ends during its education section.