Software Engineering Lead (MetaTech)
WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.
WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
The MetaTech team is the engine behind the evolution of WorldQuant's proprietary research platform — empowering Researchers and Portfolio Managers to create, deploy, and lead template trading strategies at scale. MetaTech owns both foundational infrastructure and the researcher-facing features that expand what is possible within the platform. The team responds rapidly to emerging user needs while driving long-term platform modernization, spanning simulation engine upgrades, orchestration services, caching infrastructure, and the enablement of entirely new classes of strategies.
As a Software Engineering Lead in MetaTech, you will be responsible for the technical direction of a platform that sits at the intersection of quantitative research and large-scale distributed systems. You will need deep fluency in both worlds: the ability to engage credibly with Researchers and PMs about their workflows and goals, and the technical depth to architect, deliver, and modernize the systems that power them. You will lead the team's roadmap across multiple workstreams — from expanding the range of supported strategy types to infrastructure modernization — and lead a team of engineers to implement it.
The Role
- Drive the MetaTech technical roadmap, balancing researcher-facing feature delivery with foundational infrastructure investment
- Lead architectural design and hands-on development across the platform, including simulation orchestration, caching, monitoring, and strategy lifecycle management
- Engage directly with Researchers and Portfolio Managers to understand their needs and translate them into well-scoped technical solutions
- Drive infrastructure modernization efforts, including simulation engine migrations, distributed caching, and platform observability
- Partner with cross-functional stakeholders across Research, Platform, and Operations to ensure reliable, scalable delivery
- Identify opportunities to integrate agentic workflows into existing platform systems, enabling automation of complex, multi-step research and operational processes
- Manage and mentor a team of engineers, fostering technical excellence and accountability
What You'll Bring
- Bachelor's degree in Computer Science, a related field, or equivalent job experience
- 6+ years of hands-on industry experience building scalable, high-reliability backend systems
- Deep familiarity with the Python ecosystem, particularly for data-intensive and systems-level work
- Strong systems engineering instincts: distributed computing, service orchestration, and large-scale data pipelines
- Working knowledge of quantitative investment and research concepts, with an ability to engage fluently with quant researchers and PMs
- Experience with simulation systems, financial data infrastructure, or research platform engineering is a strong plus
- Working knowledge of a Unix/Linux environment
- Excellent interpersonal and communication skills — able to bridge technical and non-technical audiences
- Excellent debugging and problem-solving skills, with a bias toward root-cause analysis over workarounds
- Solid understanding of data structures, algorithms, and system design trade-offs
- Relational and non-relational database experience
- C++ 11 (or greater) experience is a plus, particularly for simulation or performance-critical contexts
- Previous people management experience is a plus
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