1. Role Overview

This role leads the development, deployment, and optimization of a global, massive-scale financial pricing compute grid on public cloud infrastructure (AWS/GCP). The team needs this role to operationalize complex quantitative models and efficiently execute trillions of calculations for real-time risk valuation, Monte Carlo simulations, and regulatory reporting across thousands of cores. Its core purpose is to build a highly resilient, cost-optimized valuation engine that enables the firm to price its trading book rapidly and meet critical risk management deadlines.

2. Key Responsibilities

- Architect and manage distributed compute grids on public cloud platforms (AWS/GCP) to execute financial pricing models.
- Design and implement task orchestration layers to distribute millions of tasks across hundreds of thousands of CPU/GPU cores.
- Monitor, tune, and optimize platform performance, cloud cost efficiency, and resource utilization.
- Deploy, version-control, and integrate quantitative pricing models into production in collaboration with quant development teams.
- Build data logistics pipelines to deliver market data, trade data, and model configurations to runtime engines seamlessly.




- Maintain high availability, fault tolerance, and strict recovery time objectives (RTO) for the valuation engine.

3. Core Requirements & Eligibility

- Experience: 10+ years of qualified experience building and running applications on massive-scale compute grids.
- Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.
- Domain Exposure: Financial industry experience, specifically with pricing grids, Monte Carlo simulations, VaR (Value at Risk) calculations, or XVA pricing models, is highly preferred.
- Location/Setup: On-site / Hybrid work setup based in Pune or Chennai.

4. Skillset Breakdown

- Primary (Must-Have):
- Cloud Platforms: AWS or GCP
- Orchestration & Containerization: Kubernetes, Docker, AWS Batch, or GCP Batch

- Core Programming: Python
- Infrastructure & Systems: Distributed Systems, High-Performance Computing (HPC), Infrastructure-as-Code (IaC)
- Secondary (Nice-to-Have):

- GPU computing / CUDA
- Financial Quant domain (VaR, XVA, Monte Carlo)

- Serverless compute architectures
- Cloud cost management / FinOps

📌 Lead HPC Cloud Engineer (Chennai)
🏢 Straive
📍 Chennai