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Senior Equity Options Software Engineer - Remote (Wichita, KS)

Quantum Financial Solutions
Remote (Wichita, KS)
Estimated Salary
USD 140.000 – USD 180.000
New
Live Update
5 September 2026
Deadline
5 Sep 2027

Job Description

Join our elite financial engineering team as we revolutionize equity derivatives trading technology. We're urgently seeking a brilliant Software Engineer to architect and deploy high-performance systems for options pricing, risk management, and algorithmic trading platforms. This hybrid role (remote with Wichita presence) offers the rare opportunity to shape next-gen fintech solutions while enjoying flexible work arrangements. Collaborate with PhD quants and senior developers to build scalable C++/Python frameworks processing millions of transactions daily. Our competitive compensation package includes equity, unlimited PTO, and cutting-edge professional development.

Responsibilities

  • Design and implement low-latency options pricing engines in C++/Python
  • Develop real-time risk management systems for equity derivatives portfolios
  • Optimize trading algorithms using machine learning and statistical models
  • Integrate with market data feeds (Bloomberg, Refinitiv) and FIX protocols
  • Maintain high-availability Linux-based trading infrastructure
  • Lead code reviews and architectural decisions for financial systems
  • Collaborate with quants to model complex exotic option structures

Qualifications

  • 5+ years in financial software engineering, specifically options/equities
  • Expertise in C++ and Python with multithreading/async programming
  • Deep understanding of Black-Scholes, Monte Carlo, and binomial models
  • Experience with Linux kernel optimization and network socket programming
  • Strong background in low-latency systems and high-frequency trading
  • BS/MS in Computer Science, Mathematics, or Quantitative Finance
  • Familiarity with FIX protocol and market data standards

Required Skills

C++ Python Linux Financial Engineering Options Pricing Low-latency Systems Machine Learning Risk Management

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