About Client
We are a fast-moving global firm operating in the crypto market-making space (not an exchange), but focused on building next-gen high-frequency trading infrastructure for market making in various global exchanges .
A Full Stack Developer at a High-Frequency Trading (HFT) firm builds high-performance internal dashboards, low-latency APIs, and real-time risk-management tools. The role requires heavy Python backend capabilities paired with frontend engineering, focusing entirely on speed, system reliability, and microsecond data flow.
Core Responsibilities
- Backend Development: Design ultra-low latency, multi-threaded Python microservices (using FastAPI or Flask) for order routing and risk assessment.
- Frontend Engineering: Build responsive, real-time trading dashboards and admin panels using React, TypeScript, and state management (e.g., Redux) to monitor live positions.
- Data Processing: Engineer WebSocket and WebRTC pipelines to handle real-time market data streaming without bottlenecks.
- Infrastructure: Implement containerized workflows using Docker and Kubernetes, alongside CI/CD deployment pipelines.
- Cross-Functional Support: Work directly with Quantitative Researchers and Algorithmic Traders to deploy and visualize trading strategies.
Essential Qualifications
- Experience: 3 to 6 years of hands-on Python experience, with a proven track record in algo/proprietary trading, HFT firms, or fintech.
- Programming: Deep expertise in core Python, Asynchronous programming, and JavaScript/TypeScript.
- Databases: Hands-on proficiency with time-series databases (e.g., TimescaleDB), caching tools (Redis), and relational databases (PostgreSQL).
- Low Latency: Strong grasp of memory profiling, OS-level concurrency (multi-threading/multi-processing), and network latency mitigation.
Preferred Qualifications
- Basic understanding of financial markets, order books, and exchange protocols (e.g., FIX, Binance API).
- Familiarity with C++ or Rust for performance-critical backend modules.
- Degree in Computer Science, Financial Engineering, or a highly quantitative STEM field.
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