Accountabilities:
Design and build low-latency trading, pricing, risk, and analytics systems using C++, Java, or Python, ensuring performance, scalability, and reliability.
Translate quantitative models from research environments into production-grade, optimized engineering solutions.
Develop and maintain high-volume market data ingestion and normalization pipelines for real-time and historical tick data.
Build and enhance pricing engines, derivatives libraries, and risk systems including P&L attribution, scenario analysis, and stress testing tools.
Optimize critical-path systems through profiling, benchmarking, and performance tuning to reduce latency and improve throughput.
Collaborate with quants, traders, and risk teams to refine models, validate outputs, and support decision-making workflows.
Implement backtesting, simulation, and compliance reporting frameworks ensuring auditability and regulatory alignment.
Ensure system observability through robust logging, monitoring, metrics, and incident response readiness.
Contribute to architecture design, code reviews, documentation, and engineering best practices across the team.
Mentor junior engineers and help strengthen overall engineering standards and delivery quality.
Requirements:
Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative field.
6+ years of software engineering experience, preferably in fintech or capital markets environments.
Strong programming expertise in C++, Java, or Python, with experience in multiple languages preferred.
Solid understanding of financial markets, instruments, derivatives, and risk management concepts.
Proven experience building low-latency, high-throughput distributed systems.
Familiarity with market data systems, FIX protocol, and trading infrastructure.
Strong knowledge of P&L attribution, pricing models, and quantitative methods.
Experience with performance optimization, concurrency, and high-performance computing techniques.
Strong debugging, problem-solving, and analytical skills in complex systems.
Excellent communication skills with the ability to document and explain technical solutions clearly.
Benefits:
Competitive compensation aligned with US fintech market standards ($100,000 – $150,000 USD range).
100% remote work across the United States with flexible collaboration.
Direct W2 employment structure with long-term stability and growth opportunities.
Opportunity to work on high-impact trading and financial systems used in real-world markets.
Exposure to advanced quantitative modeling, risk systems, and low-latency architectures.
Career development in a highly technical fintech engineering environment.
Equal opportunity workplace with strong emphasis on diversity and inclusion.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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