Lead Engineer

Straive; Pune District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Straive in Pune seeks a senior HPC/cloud engineer to architect and operate a massive-scale cloud compute grid for financial pricing models.

You will optimize performance, cost, and reliability across AWS/GCP, using C++, Python, Docker, and Kubernetes, and collaborate with quantitative teams to push latency and throughput limits.

Qualifications

• Strong programming skills in C++ and Python for HPC workloads.
• Hands-on experience with AWS or GCP, including batch processing and containers.
• Deep expertise in Docker and Kubernetes for large-scale deployments.
• Experience designing, building, and running applications on massive-scale compute grids.
• Background in distributed systems, performance tuning and IaC principles.
• Excellent communication across quantitative research, trading and risk teams.

Responsibilities

• Architect, build, and manage a massive-scale distributed compute grid on public clouds.
• Design and implement orchestration to distribute pricing tasks across cores.
• Deploy and version control a library of pricing models for distributed execution.
• Monitor, optimize performance, cost, and resource utilization of the cloud grid.
• Collaborate with quantitative teams to integrate pricing models into the production grid.
• Engineer data logistics to ensure market/trade data and configurations are available at runtime.
• Ensure pricing engine is highly available and meets recovery objectives.

Skills

C++

Python

Cloud (AWS/GCP)

Docker

Kubernetes

Distributed systems

Performance tuning

Infrastructure as code

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

AWS

GCP

Job description

The Opportunity: Can You Build and Command a Cloud Supercomputer?

Are you interested in running one of the largest high-performance computing grids in the financial industry?

Are you interested in driving the challenge of orchestrating trillions of calculations across thousands of cloud cores to price the firm's entire trading book in minutes?

Are you interested in building the massive-scale "valuation engine" that powers next-generation risk platforms?

Key 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.

Technical Skills Needed - What We're Looking For

• Strong programming skills in languages common to high-performance computing, such as C++ and Python.
• Expert-level, hands-on 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).
• Experience in designing, building, and running applications on massive-scale compute grids.
• Prior experience in a similar role within the financial industry (e.g., running large-scale Monte Carlo simulations, VaR calculations, or XVA pricing grids) is highly desirable but not mandatory.
• A strong background in distributed systems, performance tuning, and infrastructure-as-code principles.
• Exceptional problem-solving skills, with an ability to diagnose and resolve complex issues in a high-pressure, large-scale environment.
• Excellent communication skills and the ability to work effectively with quantitative research, trading, and risk management teams.

Education:

• A degree in Computer Science, Engineering, or a related technical field.