Quantitative Developer - AI Implementation

Project Overview

We are building a cutting‑edge initiative to integrate large language models with our proprietary strategy management tools. This project aims to provide AI‑assisted insights, automate routine analytical tasks, and enable natural language interactions for portfolio managers to more efficiently analyze, maintain, and enhance trading strategies. The focus is on building foundational infrastructure, data pipelines, and a secure, user‑centric interface that protects intellectual property.

We are seeking a talented and motivated Full‑Time Software Engineer to play a key role in developing and enhancing this AI‑driven platform. You will design, build, and maintain critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform.

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs for direct data system integration, strategy analytics, and performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between internal knowledge management systems, simulation systems, and data warehouses.
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

Core Skills

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding or experience with prompt engineering principles for large language models.
• Awareness of data security and intellectual property protection considerations in AI and LLM applications.

Domain‑Specific Knowledge (Highly Beneficial)

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms.

Technical Environment Familiarity (Helpful)

• Experience working in a Linux environment.
• Knowledge of command line interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem‑solving and analytical skills.
• Strong collaboration and communication skills.
• High attention to detail and commitment to delivering high‑quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.

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World Quant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.