We are a proprietary trading and market-making firm operating across global markets, executing strategies that depend on fast, reliable decision-making and execution. We're looking for a Senior Software Engineer to design, build, and optimize the Python-based systems that power our trading operations — from market data processing and order execution to risk and monitoring.
This is a hands-on engineering role focused on building high-performance, production-grade Python systems for a latency-sensitive trading environment. You'll work closely with quantitative researchers, traders, and infrastructure engineers to keep our systems fast, reliable, and competitive.
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Design, build, and maintain trading infrastructure in Python, including market data handlers, order execution logic, and strategy runners
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Optimize Python code paths for low latency and high throughput using techniques such as asyncio, multiprocessing, vectorization (NumPy), and just-in-time compilation (Cython, Numba, or similar)
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Build and maintain tooling for research-to-production workflows, enabling quants to move strategies into live trading quickly and safely
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Develop and improve simulation, backtesting, and replay frameworks to validate strategy and infrastructure changes
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Build robust monitoring, alerting, logging, and risk-control systems for live trading
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Profile production systems to identify and resolve performance bottlenecks
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Collaborate with quant researchers to understand strategy logic and ensure efficient, correct production implementations
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Participate in incident response and on-call rotation for production trading systems
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Conduct code reviews, mentor junior engineers, and help shape engineering standards and practices
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Continuously evaluate new tools, libraries, and techniques relevant to high-performance Python systems
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3+ years of professional software engineering experience, with significant time spent on performance-sensitive or production trading systems
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Expert-level Python, including deep familiarity with the asyncio ecosystem, concurrency/parallelism patterns, and performance profiling
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Experience writing performant Python using NumPy/pandas, and optimizing hot paths with Cython, Numba, or similar tools
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Solid understanding of networking fundamentals (TCP/UDP, multicast) and how they affect latency in trading systems
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Experience with exchange connectivity or market data protocols (e.g., FIX, WebSocket APIs, REST APIs, proprietary feeds)
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Strong fundamentals in data structures, algorithms, and systems-level performance optimization
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Comfortable working in a fast-paced, low-latency production environment with high accountability
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Experience with profiling and performance analysis tools (cProfile, py-spy, line_profiler)
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Degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field (or equivalent experience)
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Prior experience at an HFT, market-making, or proprietary trading firm
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Experience interfacing Python with C/C++ extensions (pybind11, ctypes, Cython)
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Experience with high-performance messaging systems (ZeroMQ, Kafka, Redis pub/sub)
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Exposure to colocation environments, bare-metal infrastructure, and network tuning
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Familiarity with futures, options, equities, or crypto market microstructure
