Job Description
We are looking for a world-class Software Engineer to join our high-frequency trading division focused on Equity Options analytics. If you thrive in a fast-paced, quantitative environment and are passionate about building the algorithms that power the modern financial markets, this is your opportunity to shape the future of derivatives trading from our San Diego hub.
In this role, you will architect and implement the core pricing engines and risk management systems that handle millions of transactions daily. You will collaborate directly with quants and data scientists to translate complex mathematical models into robust, low-latency production code. We offer a fully remote-friendly culture within San Diego, allowing you to work from home or our state-of-the-art office.
Responsibilities
- Core Development: Design, develop, and optimize high-performance pricing models for equity options using C++ and Python.
- System Architecture: Build scalable distributed systems capable of processing real-time market data and executing trades with microsecond latency.
- Quant Integration: Work closely with quantitative analysts to implement and refine complex financial derivatives algorithms.
- Performance Tuning: Profiler and optimize existing codebases to ensure maximum throughput and minimal latency in trading environments.
- Risk Management: Develop and maintain systems to monitor and mitigate risk exposure in real-time.
- Collaboration: Mentor junior engineers and conduct code reviews to maintain high technical standards across the engineering team.
Qualifications
- Education: BS in Computer Science, Mathematics, Statistics, or a related quantitative field (Master's preferred).
- Experience: 5+ years of professional software engineering experience, preferably in FinTech, High-Frequency Trading, or Quantitative Finance.
- Technical Skills: Deep expertise in C++ (modern C++11/14/17) and Python. Experience with low-latency trading systems is highly desirable.
- Domain Knowledge: Strong understanding of financial derivatives, specifically Equity Options, Black-Scholes models, or other pricing methodologies.
- Tools: Proficient with Linux environments, Git, Docker, and message queues (Kafka, RabbitMQ).
- Problem Solving: Exceptional ability to solve complex mathematical and algorithmic problems under pressure.