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Utilize and interact with agentic systems, including planning algorithms, memory architectures, reflection mechanisms, and collaborative reasoning patterns that support autonomous decision-making in quantitative trading environments. Fine-tune genetic algorithms hyperparameters to optimize adaptive system performance, decision-making quality, and contribute to deep learning model development for the PM model layer and custom agentic workflows. Responsible for portfolio management: take risk, manage P&L, and make trading decisions within defined risk parameters while developing expertise in quantitative portfolio management principles. Utilize agentic systems, deploying and working with cognitive reasoning systems for quantitative modeling problems, leveraging planning, tool use, memory, reflection, and collaboration capabilities Contribute to machine learning model building for PM model layer applications specific to portfolio management objectives Build and customize agentic workflows and tools tailored to portfolio management needs and specific trading strategies Execute human-in-the-loop decisions and checks ensuring that traded strategies meet quant trading acceptance criteria This position combines portfolio management with cutting-edge agentic AI technology. 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