We are looking for a talented Quantitative Developer to join our Investment Technology team, working at the intersection of software engineering, quantitative finance, and portfolio management. You'll play a key role in building, enhancing, and maintaining the systems that power investment decision-making, risk management, and portfolio construction across the firm.

This is an excellent opportunity for someone who enjoys solving complex technical problems in a fast-paced asset management environment, working closely with portfolio managers, quantitative researchers, risk teams, and traders.

1. Design, develop, and maintain core components of our Portfolio Management System (PMS), including order management, position keeping, risk analytics, and performance attribution modules
2. Collaborate with portfolio managers and quant researchers to translate investment strategies and models into robust, production-grade code
3. Build and optimise pricing, risk, and analytics libraries across asset classes (equities, fixed income, derivatives, multi-asset)
4. Integrate the PMS with internal and external systems (market data feeds, execution management systems, custodians, compliance platforms)
5. Improve system performance, scalability, and data integrity across the investment technology stack
6. Automate workflows for rebalancing, trade generation, compliance checks, and reporting
7. Support the migration/enhancement of legacy systems and contribute to architecture decisions
8. Provide production support and troubleshoot issues affecting portfolio managers and traders in real time
9. Write clean, well-tested, and well-documented code following best engineering practices

Essential:

1. Strong programming skills in Python, C#, C++, or Java (please specify your primary stack)
2. Solid understanding of financial instruments (equities, fixed income, derivatives) and portfolio management concepts (NAV, P&L, risk metrics, performance attribution)
3. Experience working with or building portfolio/order management systems (e.g., Aladdin, Charles River, Bloomberg AIM, SimCorp Dimension, Enfusion, or proprietary systems)
4. Strong SQL and experience working with large financial datasets
5. Solid grasp of software engineering fundamentals: version control (Git), testing, CI/CD, design patterns
6. Excellent problem-solving skills and attention to detail
7. Strong communication skills, with the ability to work closely with both technical and investment teams

Desirable:

1. Experience with market data providers (Bloomberg, Refinitiv, FactSet)
2. Familiarity with risk and analytics libraries (e.g., QuantLib) or vendor risk systems (Barra, Axioma, MSCI)
3. Exposure to cloud infrastructure (AWS/Azure) and containerisation (Docker/Kubernetes)
4. Knowledge of FIX protocol and trade execution workflows
5. Degree in Computer Science, Mathematics, Engineering, Financial Engineering, or a related quantitative field