Quantitative Developer

Technologists at WorldQuant research, design, code, test and deploy projects while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: We are looking for an exceptionally strong software engineer to join our Technology organization at WorldQuant. You will be part of a business-facing team responsible for building and evolving the core systems that power our Quant strategies. This is an AI-forward team: large language models (LLMs) and AI agents are part of our daily workflow — from writing and reviewing code, to automating operational toil, to building internal copilots and agentic tools that the whole team relies on. You won't just use AI to move faster; you'll help shape how it's applied across our engineering practice.

Design and build data pipelines and the data layer.

Develop and maintain the computational frameworks and infrastructure that run our quantitative strategies at scale.

Implement and enhance quant-related software systems for data, research, portfolio construction, and trading.

Work closely with Researchers, and Quants as a hands-on engineering partner, helping them turn ideas into robust production solutions.

Gain exposure to the full lifecycle of the systematic/quant business, from data ingestion through research, implementation.

Build and integrate AI-powered tooling - LLM agents, copilots, and automation - into engineering and research workflows.

Use AI coding assistants and agentic developer tools to ship higher-quality software faster.

What You’ll Bring:

Degree in a technical or quantitative discipline from a top tier institution.

3 to 8 years of working experience in software engineering.

Demonstrated ability to program in Python (preferred) or C++ on Linux/Unix platforms, familiarity with scripting languages.

Experience with effective code version control, as well as Continuous Integration and Deployment.

Exceptional communication skills in both verbal and written form.

Excellent problem-solving abilities and judgment with strong attention to detail.

Mature and thoughtful, with the ability to operate in a collaborative, team-oriented culture.

Motivated by the transformational effects of technology-at-scale.

Experience with AI technologies, such as LLMs and agentic AI, along with their use cases would be beneficial.

Experience in finance is a plus but not required.