Quant System Engineer (C/C++)

Role Overview:

We are hiring a Quant Systems Engineer to build and maintain performance-critical

components of our trading and analytics stack. You will work closely with quant researchers

and portfolio managers to transform models into reliable, production-ready trading systems.

This is not a web or UI role. The focus is on systems engineering, data pipelines, and

real-time processing.

Key Responsibilities:

● Trading & Market Data Systems

● Design and implement C/C++ services for live trading, market data handling, and analytics.

● Build event-driven systems that process tick and bar data with millisecond-level latency.

● Develop reliable order management and execution workflows with strong correctness guarantees.

● Handle high-volume intraday data with predictable performance and minimal data loss.

Performance-Oriented Engineering

● Optimize for consistent latency, throughput, and system stability rather than ultra-low latency.

● Profile and tune CPU, memory, and concurrency bottlenecks in production systems.

● Design efficient data structures for time-series and event-based workloads.

● Systems Architecture & Reliability

● Build systems that run continuously during market hours with graceful failure handling.

● Design fault-tolerant pipelines for market data ingestion and strategy execution.

● Work extensively on Linux-based systems, process management, and operational tooling.

Quant Collaboration

● Partner with quant researchers to productionize trading strategies.

● Build internal libraries and APIs used for back testing, live execution, and monitoring.

● Help bridge research code and live trading infrastructure.

Required Qualifications:

● Strong experience in C and C++.

● Excellent grasp of data structures, algorithms, and system design fundamentals.

● Experience with multithreading, concurrency models, and asynchronous systems.

● Comfortable working in Linux environments and debugging production issues.

● Ability to think in terms of system trade-offs, failure modes, and scale