Jobs at Citadel Securities

Build high-performance, workflow-driven client interfaces for institutional electronic trading platforms using TypeScript and React. Integrate front-end applications with C++, Python, distributed backend services, real-time data, and data pipelines. Translate complex trading and market-data workflows into intuitive experiences, optimize performance, establish UI engineering best practices, and contribute to reusable frameworks, component libraries, and developer tooling while collaborating with product, business, quantitative research, and engineering teams.

Conduct quantitative research for automated trading strategies by developing mathematical models, translating algorithms into code, backtesting trading signals, analyzing unconventional data, and refining monetization systems. Collaborate with senior researchers during an 11-week post-doctoral internship while applying advanced probability, statistics, machine learning, and time-series techniques to financial markets.

Develop and evolve investor-facing equities products using React and TypeScript. Partner with investors, product managers, UX designers, and engineering teams to understand workflows, prototype solutions, and deliver high-performance, data-intensive interfaces for research, risk analytics, portfolio analysis, and investment decisions. Own products end to end, from identifying user needs through launch and iteration, while maintaining high standards for quality, testing, performance, and maintainability.

Build the core visualization platform, reusable frameworks, design systems, and developer tooling for client-facing financial analytics. Translate complex market and trading data into clear, high-performance applications while partnering with product, design, sales, and engineering teams. Evaluate emerging technologies, provide hands-on technical leadership, conduct design reviews, and mentor engineers. The role requires strong software engineering, visual design judgment, interaction design, and information architecture expertise.

Lead architecture and engineering of high-performance crypto market feed handlers and exchange connectivity. Build low-latency ingestion, normalization, sequencing, order book construction, and distribution systems; drive venue onboarding, data quality, reconciliation, recovery, and replay; improve latency, throughput, resiliency in a 24/7 production environment; partner with trading and research teams; mentor engineers and define operational KPIs.

Support rates sales and trading desk by booking and reconciling trades, managing risk breaks, automating operational workflows with developers, coordinating releases and testing, and liaising with Trading, Technology, Compliance, Operations, Accounting and Business Management to deploy new trading capabilities and support day-to-day operations.

The Market Data Engineer will design and implement high-performance market data systems, focusing on trading infrastructure, performance optimization, and system resiliency.

Recruiting Coordinators support full-cycle recruitment processes, manage candidate interactions, and work on HR projects, all while building stakeholder relationships.

The role involves building and supporting production-level trading systems in C++ for credit and rates products, collaborating with traders and quantitative researchers.

Build full-stack, low-latency trading and pricing tools for options traders. Collaborate with traders, researchers, and business stakeholders to design intuitive frontends and scalable backend services, prototype and productionize distributed systems, and expand trading capabilities globally while improving performance, stability, and usability.

Design, implement, and maintain low-latency, high-performance network infrastructure for trading systems. Partner with engineering teams to automate, monitor, and troubleshoot distributed networks, optimize performance, ensure resilience and security, and evaluate emerging technologies to improve scalability and reliability.

Build and optimize low-latency, high-performance C++ trading systems for crypto markets; partner with researchers and traders to productionize strategies; optimize latency, throughput, reliability; implement pricing, risk, and execution logic; analyze large-scale market and trade data; ensure resilience, testing, and scalability across global venues.

Analyze financial markets and securities using fundamental and quantitative research. Develop sector expertise, identify pricing inefficiencies, transform unstructured data into signals, monitor market trends, and collaborate with traders to create actionable trade ideas during an 11-week internship.

Build high-performance trading tools and large-data research platforms in small teams. Design system architectures, develop resilient production software, and apply distributed computing, NLP, and machine learning to solve complex quantitative problems while collaborating with engineers, traders, and researchers.

Join as an FPGA engineering intern to design, implement, and test FPGA solutions for ultra-low latency trading systems. Improve system efficiency and performance via RTL coding, synthesis, simulation, and hardware validation while collaborating in small teams with engineers and business stakeholders.

As a Software Engineer in Test, you'll build Python frameworks and C++ hooks to verify system correctness, accelerate CI/CD, and manage performance testing across equities.

11-week software engineering internship building high-performance research platforms and trading tools. Work in small teams to design systems, develop platforms and web frameworks, and apply distributed computing, NLP and machine learning. Collaborate with senior engineers, network with peers, and contribute code that rapidly moves into production.

As a PhD intern, you will develop and test trading strategies, perform statistical analysis, and collaborate with senior researchers.

Conduct research and develop automated trading strategies using advanced statistical techniques and programming skills. Collaborate in a fast-paced team to innovate and implement quantitative models.

Conduct rigorous research using statistics and machine learning to extract patterns from datasets. Implement algorithms, back-test models, and document findings.