Research and Portfolio Management Engineering

About the role

AQR is looking for a Research and Portfolio Management Engineering specialist to strengthen their quantitative operations in Greenwich, Connecticut. This position centers on designing and maintaining the software infrastructure that powers research analysis and portfolio construction workflows. The engineer will partner with quantitative researchers and portfolio managers to turn mathematical models and trading strategies into dependable, scalable software systems. Candidates should bring a solid foundation in computer science or a related field, along with a genuine interest in applying technology to financial markets. The role demands both independent problem-solving and the ability to collaborate across multidisciplinary teams within the firm.

Key facts

What you'll do

1. Design and build data pipelines that ingest market data from multiple exchanges and normalize it for research use.

2. Develop and maintain backtesting frameworks that allow researchers to evaluate trading strategies against historical market conditions.

1. Create visualization dashboards that present portfolio risk metrics, exposure breakdowns, and performance attribution to portfolio managers.

4. Implement risk monitoring systems that track portfolio exposures in real time and flag breaches of predefined limits.

5. Collaborate with quantitative researchers to translate mathematical models into efficient, well-tested software implementations.

6. Optimize execution algorithms and order management workflows to reduce latency and improve trade fill rates.

7. Write unit and integration tests to ensure the correctness and reliability of all production systems.

8. Maintain and extend the firm's proprietary research platform used for analyzing large-scale financial datasets.

9. Troubleshoot and resolve issues in live trading systems, coordinating with operations teams to minimize downtime.

10. Document system architectures and codebases so that team members can understand and build upon existing work.

11. Participate in code reviews and contribute to engineering standards that govern the development process across teams.

12. Refactor legacy codebases to improve system performance, reduce technical debt, and ensure long-term maintainability of the engineering platform.

Requirements

1. Bachelor's degree in computer science, engineering, mathematics, or a related quantitative discipline from an accredited institution.

2. Three or more years of professional software engineering experience building systems that process financial or market data.

3. Proficiency in at least one general-purpose programming language such as Python, C++, or Java for production systems.

4. Experience working with relational databases and SQL to query, transform, and manage large volumes of structured data.

5. Familiarity with version control systems, continuous integration practices, and modern software development workflows in a team setting.

6. Strong understanding of statistical methods, linear algebra, and probability theory as applied to financial data analysis.

7. Ability to communicate complex technical concepts clearly to both engineering colleagues and non-technical business stakeholders.

8. Demonstrated attention to code quality, including writing clean, modular, and well-documented software that is easy to maintain.

9. Experience presenting research findings and engineering recommendations to senior leadership and investment committee members in a clear and concise manner.

Nice to have

1. Master's degree or PhD in a quantitative field such as computer science, financial engineering, or applied mathematics.

2. Prior experience with distributed computing frameworks like Apache Spark or Hadoop for processing large-scale financial datasets.

3. Knowledge of low-latency system design and high-frequency trading infrastructure patterns used in electronic markets.

4. Familiarity with cloud platforms such as AWS or GCP for deploying and scaling data processing applications.

Skills & tools

1. Python for data analysis, scripting, and building internal tools used by research and portfolio management teams.

2. C++ for performance-critical components that require low-latency execution in trading and risk systems.

3. SQL and database design for managing structured financial data across multiple storage systems.

4. Git for source code management, branching strategies, and collaborative development workflows.

5. Linux command line and shell scripting for server administration and automation tasks.

6. REST APIs and microservices architecture for connecting research tools with portfolio management applications.

Practical notes

1. This role is based in the Greenwich, Connecticut office and requires on-site presence during regular business hours.

2. Candidates must be authorized to work in the United States, as the firm does not sponsor visas for this position.

3. The hiring process includes a technical interview covering programming, data structures, and problem-solving, followed by a system design discussion.

4. AQR values candidates who demonstrate intellectual curiosity, rigorous analytical thinking, and a collaborative approach to solving complex problems.

5. Applications should include a resume and any relevant links to published work, open-source contributions, or technical portfolios.