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 backtesting, 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.
Preferred / Nice to Have
-Prior experience with quant trading, fintech, or real-time financial systems.
-Familiarity with market data formats, tick data, OHLC bars, or intraday analytics.
-Experience designing event-driven or streaming architectures.
-Exposure to Python for research integration or orchestration.
-Tier-1 engineering college background preferred.
What We Offer
-Direct ownership of live trading systems used by a quant fund.
-Exposure to real market behavior and production constraints.
-Collaboration with a focused, research-driven quant team.
-Engineering culture that values clarity, robustness, and fundamentals.
-Competitive compensation with performance-linked upside.