Remote Quant Developer, FinTech - Low-Latency Trading

Bright Vision Technologies; Farmington Hills (MI); On-site; USD 89,000 - 112,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced Quant Developer (FinTech) to build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. In this role you will partner closely with quants and traders to translate mathematical models into production-quality software that meets strict performance, accuracy, and operational requirements.

The ideal candidate will combine strong software engineering skills with solid quantitative fundamentals and deep

Qualifications

• Minimum 7+ years of software engineering experience, preferably in fintech.
• Bachelor’s or Master’s degree in CS, Math, Physics, or related quantitative field.
• Strong programming skills in C++, Java, or Python (at least two).
• Knowledge of financial markets, instruments, and risk management.
• Experience building low-latency, high-throughput systems.
• Familiarity with market data systems and FIX protocol.

Responsibilities

• Partner with quants and traders to translate models into production software.
• Design and optimize low-latency trading, risk, and analytics components.
• Lead code reviews and performance tuning for reliability.
• Document software designs and system interfaces.

Skills

Software Engineering

Fintech domain knowledge

Low-latency systems

Concurrency

Debugging & profiling

Communication

Education

Bachelor’s or Master’s in CS/Math/Physics

Tools

FIX protocol

QuantLib

kdb+/q

GPU pricing (conceptual)

Cloud-native architectures

Job description

Bright Vision Technologies is seeking an experienced Quant Developer (FinTech) to build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. In this role you will partner closely with quants and traders to translate mathematical models into production-quality software that meets strict performance, accuracy, and operational requirements.

The ideal candidate will combine strong software engineering skills with solid quantitative fundamentals and deep