Senior Quantitative Software Engineer - Fixed Income Platforms

The Opportunity A leading New York-based structured credit investment firm is undertaking a major technology initiative to build a next-generation scalable quantitative computing and analytics platform . We are seeking a senior, hands-on software engineer with demonstrated experience designing and developing large-scale financial computing platforms, reusable analytical libraries, and high-performance quantitative systems . The platform will support pricing, valuation, forecasting, risk analysis, and investment research across a broad range of fixed-income and structured-credit products. This is a core platform engineering role—not a traditional desk-modeling, application-development, or general data engineering position. Key Responsibilities Design and build scalable quantitative computing infrastructure supporting multiple financial models, users, and investment applications. Develop reusable pricing, valuation, and analytical libraries and shared computational services. Architect distributed and parallel computing frameworks to significantly improve analytical processing speed and capacity. Build scalable data services, pipelines, and APIs supporting computationally intensive financial analytics. Modernize existing quantitative infrastructure using cloud computing, containerization, and modern software engineering practices. Improve system performance, scalability, reliability, testing, and deployment. Collaborate directly with quantitative researchers and investment professionals to translate complex fixed-income analytical requirements into scalable production systems. Required Qualifications 5+ years of hands-on software engineering experience, including substantial experience building complex, scalable computing platforms or shared analytical libraries . Demonstrated experience designing and developing large-scale computational systems—not solely individual trading desk models or applications. Strong understanding of fixed-income products, bond analytics, pricing, valuation, or financial risk modeling . Experience with distributed computing, parallel processing, high-performance computing, or scalable numerical analytics. Strong programming skills in Python, C++, C#, or Java , with demonstrated software architecture and production development experience. Experience developing reusable software components and systems supporting multiple models or applications. Familiarity with cloud computing, distributed systems, and modern software development practices. Highly Desirable Experience building pricing libraries, valuation engines, risk calculation platforms, or large-scale quantitative analytics systems. Knowledge of structured credit, securitized products, mortgage-backed securities, or other complex fixed-income instruments. Experience with GCP, AWS, Kubernetes, Docker, CI/CD, and cloud-native computing. Background in quantitative finance, numerical computing, or financial engineering. Experience integrating AI/ML technologies into quantitative research or analytics infrastructure. Why This Opportunity Is Different This is an opportunity to play a key engineering role in a multiyear initiative to modernize the core quantitative technology of a sophisticated investment firm. The successful candidate will help build the shared computing libraries, analytical engines, and scalable infrastructure that enable investment professionals to analyze more assets, run more complex models, and make investment decisions faster. Keywords: Quantitative Software Engineer, Quantitative Developer, Fixed Income Analytics, Pricing Libraries, Distributed Computing, Parallel Computing, High-Performance Computing, C++, Python, C#, Java, Scalable Computing, Quantitative Platforms, Cloud Computing, Structured Credit. Please send resume to Jim Geiger Analytic Recruiting