Quant Trading Systems Engineer

Quant Trading Systems Engineer Responsibilities Design, develop, and continuously optimize low-latency quantitative trading systems, including market data connectivity, strategy execution, order routing, exchange connectivity, trading gateways, and related core modules. Design and develop risk control systems, including real-time risk management, pre-trade checks, trading limits, anomaly detection, circuit breakers, risk monitoring, and alerting mechanisms. Drive deep performance optimization across the trading system stack, minimizing latency across critical paths such as network communication, memory management, concurrency models, serialization, garbage collection, lock contention, and system calls. Work closely with quantitative researchers, traders, and infrastructure teams to translate strategy requirements into stable, efficient, and production-ready trading capabilities. Contribute to system reliability and resilience, including high-availability architecture, failover and recovery mechanisms, monitoring and alerting, stress testing, replay, and issue diagnosis. Track and evaluate emerging technologies applicable to low-latency trading systems, and continuously improve system architecture and engineering efficiency. Requirements 5–8 years of backend systems development experience. Experience in trading systems, quantitative trading, matching engines, market data systems, risk systems, or other low-latency systems is strongly preferred. Strong proficiency in at least one of Java, Kotlin, Scala, Rust, or C++, with solid engineering fundamentals and system design capabilities. Familiarity with high-performance and low-latency system development, including concurrent programming, network programming, memory models, performance profiling, and optimization techniques. Good understanding of common trading system workflows, including market data processing, order management, trade execution, risk checks, and execution reports. Strong focus on latency, throughput, stability, and observability, with the ability to identify and resolve complex performance bottlenecks. Strong analytical skills, high standards for code quality, and proven ability to deliver robust engineering solutions. Ability to quickly learn new technologies, business domains, and technical concepts, and to execute effectively in a fast-paced, high-intensity environment. Nice to Have Experience with digital assets, equities, futures, FX, market making, high-frequency trading, or other quantitative trading systems. Experience with low-latency network communication, kernel bypass, DPDK, RDMA, FIX protocol, exchange gateways, or matching engine development. Familiarity with JVM performance tuning, C++/Rust performance optimization, lock-free programming, CPU cache optimization, NUMA, asynchronous I/O, and related low-level performance topics. Experience with real-time risk controls, capital risk controls, position risk controls, account-level risk controls, or trade anomaly detection systems. Experience building large-scale distributed systems, high-availability systems, or real-time data processing systems. What We Are Looking For We are looking for someone who can not only write high-quality code, but also think deeply from the perspectives of system architecture, runtime performance, trading workflows, and business risk. You are sensitive to latency, care about engineering details, and are motivated to continuously push the boundaries of system performance. You should be able to learn and deliver consistently in a fast-moving trading environment.