Risk Analytics Engineer - Cloud-Scale Pricing Grid Lead

Capgemini; New Jersey; Hybrid; USD 103,000 - 129,000; Full time

Benefits offered by this job

Paid time off

Health insurance

Retirement plans

Life and disability insurance

Employee assistance

Job summary

Capgemini is seeking a lead for the Pricing Engine in New Jersey to architect and operate a massive-scale, distributed compute grid on public clouds. You will implement orchestration across millions of tasks, ensure accuracy with market and trade data, and integrate pricing models for fast, reliable risk valuation.

This role requires 10+ years in high-performance computing, deep cloud expertise, and strong programming skills in C++ and Python, with experience in finance risk pricing.

Qualifications

• 10+ years of professional experience designing and running large-scale compute grids.
• Expert level in AWS or GCP with batch processing, containers, and serverless.
• Deep expertise in Docker and Kubernetes.
• Strong programming skills in C++ and Python.
• Experience with Monte Carlo simulations, VaR or XVA pricing grids in finance (desirable).
• Degree in Computer Science, Engineering, or related field.
• Distributed systems, performance tuning, and IaC background.
• Excellent problem-solving and communication skills.

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 CPU/GPU 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.

Skills

Massive-scale compute

Public cloud (AWS/GCP)

Docker & Kubernetes

C++ & Python

Distributed systems

Financial risk pricing

Education

Bachelor's in Computer Science or related

Tools

Batch processing frameworks

Serverless platforms

Job description

Capgemini is seeking a lead for the Pricing Engine in New Jersey to architect and operate a massive-scale, distributed compute grid on public clouds. You will implement orchestration across millions of tasks, ensure accuracy with market and trade data, and integrate pricing models for fast, reliable risk valuation.

This role requires 10+ years in high-performance computing, deep cloud expertise, and strong programming skills in C++ and Python, with experience in finance risk pricing.