Position Overview
We are looking for a Quantitative Developer to build and optimize high-performance trading systems with a focus on trade execution, order management systems (OMS), and low-latency infrastructure. You will work closely with traders, quants, and infrastructure teams to design systems that directly impact trading performance and PnL.
Key Responsibilities
- Design and develop low-latency trade execution systems and order management systems (OMS)
● Build and optimize high-frequency trading (HFT) infrastructure for performance and scalability
● Develop exchange connectivity, execution gateways, and market access components
● Improve network performance and latency through kernel/network stack optimizations
● Build and maintain real-time data pipelines for market data ingestion and processing
● Work on multithreaded and distributed systems for high-throughput environments
● Collaborate with quant researchers and traders to translate strategies into production systems
● Perform performance profiling, benchmarking, and system tuning
● Ensure system reliability, fault tolerance, and monitoring in live trading environments
Requirements
Requirements
- 3–5 years of experience in quantitative development / low-latency systems / trading infrastructure
● Strong programming skills in C++ (preferred) or Java/Python (performance-critical systems exposure required)
● Hands-on experience with Trade execution systems / OMS, HFT or low-latency trading systems, exchange connectivity (FIX, binary protocols, market data feeds)
● Solid understanding of multithreading, concurrency, and memory optimization, linux systems programming, network programming (TCP/UDP, sockets, kernel bypass – DPDK/Solarflare is a plus)
● Experience in network optimization and latency reduction techniques Quantitative Developer
● Exposure to real-time data pipelines / streaming systems
● Strong problem-solving and debugging skills in performance-critical environments
Benefits
- Work on cutting-edge low-latency trading systems
● Direct impact on trading performance and revenue generation
● High learning curve with exposure to quant research + execution stack
● Competitive compensation with performance-linked upside
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