Responsibilities

• Lead the design and development of system architecture for trading, backtesting, risk control, and capital management
• Optimize the distributed backtesting framework to support high-frequency factor computation and large-scale historical data validation
• Build a comprehensive system monitoring stack to keep the production trading environment stable
• Work closely with the strategy team to deliver high-performance backtesting platforms and trading systems

Requirements

• Bachelor's degree or above from a top university in mathematics, computer science, financial engineering, or related STEM fields; 3+ years of experience
• Expert in C++ with proven ability to develop large-scale codebases
• Industry-agnostic — experience with large-scale infrastructure projects is a plus (distributed computing, storage, deep learning platforms, etc.)

Responsibilities · Strategy Implementation & Optimization

• Implement quantitative trading strategies for equities, futures, options, and innovative financial products, translating researchers' logic into efficient, robust C++ code
• Profile and optimize existing strategies to reduce latency and improve execution efficiency
• Contribute to the development and maintenance of the strategy backtesting system, ensuring accurate and reliable results

Responsibilities · Low-Latency Trading Systems

• Design, develop, and maintain high-performance low-latency trading systems spanning order management, risk management, market data processing, and exchange connectivity
• Optimize system architecture to eliminate latency from thread contention, memory allocation, and system calls
• Integrate and maintain exchange market data and trading interfaces (CTP, UST, FIX, etc.)

Responsibilities · Data Processing & Analytics

• Design and maintain high-performance data pipelines for tick-level and millisecond market data
• Build tooling for data cleaning, alignment, and factor computation, providing high-quality data for strategy research

Responsibilities · Stability & Monitoring

• Establish monitoring and alerting for trading systems to keep production trading running stably
• Rapidly diagnose and resolve live system issues; participate in incident reviews and improvements

Responsibilities · Research & Innovation

• Track frontier technologies — new C++ standards, low-latency techniques, hardware acceleration (FPGA, DPDK) — and drive continuous system evolution
• Contribute to the quantitative trading framework and toolchain, raising the team's overall R&D efficiency

Requirements · Education & Experience

• Bachelor's degree or above in computer science, software engineering, mathematics, physics, or related fields
• 3+ years of C++ development experience; quantitative trading, HFT, or low-latency systems experience preferred

Requirements · Technical Skills

• Expert in C++11/14/17; familiar with STL, template programming, multithreading, memory management, and performance tuning
• Comfortable developing and debugging on Linux (GCC / GDB / Perf / Valgrind); proficient in Shell / Python scripting
• Solid network programming skills (TCP/IP, Socket, ZeroMQ) with a deep understanding of low-latency network optimization
• Familiarity with trading interface protocols (CTP, FIX, Binary, etc.) is a plus
• Familiarity with quantitative strategy concepts (factors, backtesting, risk control) is a plus

Requirements · General Qualities

• Good engineering habits — clear, maintainable, testable code; familiar with Git and CI/CD workflows
• Strong problem analysis and localization skills; able to resolve complex system issues under pressure
• Genuine interest in quantitative trading; strong teamwork and communication skills

Nice to Have

• Experience building proprietary low-latency trading frameworks or middleware
• Familiarity with time-series databases such as KDB+/q or ClickHouse
• Experience at a top quantitative hedge fund or proprietary trading firm

Responsibilities

• Participate in designing and building high-performance trading systems, distributed backtesting platforms, real-time risk control, and core capital management architecture
• Under guidance, optimize the large-scale distributed backtesting framework — supporting high-frequency factor computation, massive historical data simulation, and faster strategy iteration
• Help build end-to-end system monitoring to ensure high availability and stability of the production trading environment, and quickly locate performance bottlenecks
• Under guidance, work deeply with the strategy research team to build an integrated low-latency, high-throughput backtesting and trading platform, and explore the engineering deployment of AI models in trade execution and signal generation

Requirements

• Bachelor's degree or above from a top university in computer science, software engineering, mathematics, financial engineering, or related STEM fields (CS preferred)
• Strong C++ skills; familiar with C++17/20; solid data structures and algorithms; experience with large-scale codebases and performance tuning
• Familiar with Linux systems programming, network programming, and multithreaded concurrency, with good engineering habits
• Experience with large-scale infrastructure projects is a plus (distributed computing / storage, HPC, deep learning training platforms, etc.)
• Final-year students and interns are welcome; we provide a complete mentorship and hands-on growth program

Nice to Have

• ICPC / CCPC regional silver medal or above
• AI development experience; familiar with TensorFlow / PyTorch; understanding of model inference optimization or reinforcement learning applications in finance

Responsibilities · Test Frameworks & Tooling

• Design and develop automated testing frameworks for quantitative trading systems, covering unit, integration, stress, and regression testing
• Build simulated trading environments for end-to-end strategy and system testing, ensuring model-to-execution consistency
• Develop performance testing tools to precisely measure latency, throughput, and jitter

Responsibilities · Trading System Quality

• Own quality assurance for the core trading engine, order management system (OMS), risk control, and market data gateways
• Design test cases for high-frequency trading scenarios covering edge cases, failure modes, and concurrency conflicts
• Participate in code reviews, advising on testability and robustness

Responsibilities · Backtest & Strategy Validation

• Build validation mechanisms for the backtesting framework to ensure live-backtest consistency; identify and fix the backtest-to-live gap
• Help quantitative researchers verify strategy logic — factor computation, signal generation, and order execution correctness

Responsibilities · CI/CD & Quality Infrastructure

• Build CI/CD pipelines for automated build, test, and deployment on every commit
• Establish quality metrics — coverage, defect rate, system stability — and drive continuous improvement
• Participate in production incident reviews and write regression tests to prevent recurrence

Requirements · Education

• Bachelor's degree or above in computer science, software engineering, electronic engineering, automation, or related fields

Requirements · Professional Skills

• Proficient in Python, C++, or Java, with good code style and design pattern awareness
• Familiar with mainstream test frameworks (pytest, Google Test, JUnit); experience building test automation frameworks
• Skilled with CI/CD tooling such as Git, Jenkins, and Docker
• Solid SQL; familiarity with time-series databases (ClickHouse, InfluxDB) is a plus

Requirements · Experience

• 5+ years in test development or software development (flexible for junior roles)
• Experience testing financial trading systems, quantitative platforms, or low-latency systems preferred
• Experience with performance testing, chaos engineering, or stability engineering preferred

Requirements · General Qualities

• Relentless pursuit of quality with strong ownership and risk awareness
• Rigorous logic; adept at spotting edge cases and latent issues
• Strong communication skills across engineering, research, and trading teams

Nice to Have

• Knowledge of financial trading — order types, market microstructure, the FIX protocol
• Experience with chaos engineering tools (Chaos Mesh, Gremlin) or production stability drills
• Experience developing or validating quantitative backtesting systems
• CFA Level I passed, or an equivalent finance background