Enhance an AI-powered crypto and multi-asset investment engine

Crypto United Partners is seeking a senior quantitative investment product engineer to complete, audit, and enhance our institutional-grade crypto and multi-asset investment engine ahead of launch. You will work at the intersection of quantitative finance, data science, and product design, ensuring our strategies are robust, scalable, and aligned with institutional standards. This is a hands-on, high-impact role for an entrepreneurial quantitative product strategist who combines deep financial expertise with advanced technical skills and a proven track record of designing and launching investment strategies. The ideal candidate holds an advanced degree in Finance, Economics, Financial Engineering, Mathematics, Computer Science, or a related field, with 7+ years of experience in quantitative research, product origination, or strategy design within asset management, banking, or trading. You bring proven experience launching systematic investment strategies or structured products, hands-on knowledge of crypto assets and blockchain ecosystems, and advanced proficiency in Python, SQL, and data pipeline management. Familiarity with machine learning frameworks (TensorFlow, PyTorch, XGBoost) and classic portfolio construction models (mean-variance, risk parity, factor models etc.) is essential, as is a deep understanding of portfolio theory, risk management, and the regulatory and operational requirements for institutional products. This mission is far beyond data management or pure coding and requires a solid interest and affinity for investments and financial markets. In this role, you will also design and refine systematic investment strategies, audit and stress-test our existing ML-driven investment engine, and build predictive models, dashboards, AI agents, and automation workflows for signal generation and reporting. We offer the challenge and opportunity to shape with us the next-generation institutional crypto and traditional asset management platform.