The Front Office Technology team builds and supports internal technology solutions used by Portfolio Managers, Traders, Risk teams and Execution desks within a global investment firm.

The team develops and operates a range of quantitative and trading applications covering pricing, risk analytics, market data, portfolio monitoring and workflow automation.

The role involves a combination of structured platform development and rapid delivery of analytical solutions directly requested by front-office stakeholders. Developers work closely with investment professionals to understand business needs, design solutions and deliver tools that improve trading and investment workflows.

Join a small, collaborative Front Office Development team responsible for building and enhancing quantitative and trading applications.

This role focuses on Rapid Application Development (RAD), where you will partner closely with Portfolio Managers, Traders, Quants and Risk teams to translate investment and trading requirements into practical technology solutions.

The successful candidate will combine strong software engineering capabilities with an interest in financial markets, developing applications that support pricing, risk management, portfolio analytics, market data analysis and trading workflows.

The role requires strong problem-solving and system design skills, including the ability to understand complex requirements, define technical approaches and deliver scalable solutions in a fast-paced front-office environment.

The team increasingly adopts AI-assisted development tools to accelerate delivery. Developers are expected to leverage these tools effectively while maintaining strong engineering standards through architecture design, code review and quality assurance.

1. Design, develop and maintain internal trading applications and analytical tools used by Portfolio Managers, Traders, Risk teams and Execution desks.
2. Build Python/FastAPI backend services supporting quantitative calculations and front-office workflows.
3. Develop React/TypeScript user interfaces for trading applications, including risk dashboards, rates monitoring tools, P&L analytics and portfolio views.
4. Work directly with front-office stakeholders to understand requirements, prototype solutions and deliver tools that support investment and trading decisions.

1. Work with proprietary quantitative libraries and pricing engines, including Python interfaces to C++/.NET based analytics frameworks (training provided).
2. Develop and enhance quantitative applications supporting pricing, risk analytics and portfolio analysis.
3. Build and maintain risk management tooling, including VaR analytics, scenario analysis, pricing tools and legacy system replacements.
4. Support quantitative workflows such as market monitoring tools, P&L attribution analysis, backtesting prototypes and investment analytics.
5. Support market data integration and trading workflow processes.

1. Contribute to the development and enhancement of internal front-office trading platforms.
2. Build reliable APIs, services and applications supporting investment workflows.
3. Work with cloud infrastructure including containerisation, caching solutions and monitoring/observability tooling.
4. Collaborate with engineering teams to ensure applications are scalable, maintainable and aligned with architectural standards.

1. Work directly with Portfolio Managers, Traders, Quants and Risk professionals to understand business requirements and deliver solutions efficiently.
2. Handle both structured development projects and fast-paced ad-hoc requests requiring independent problem solving.
3. Support daily and weekly business-as-usual processes where accuracy and reliability are critical.
4. Investigate issues involving pricing, market data, risk calculations and P&L analysis.

1. Strong software engineering and system design skills, with the ability to translate complex business requirements into practical technical solutions.
2. Strong Python development experience, particularly in backend services, analytical applications or quantitative tooling.
3. Experience developing front-end applications using React and TypeScript.
4. Comfortable working directly with front-office stakeholders, including Portfolio Managers, Traders, Quants and Risk teams.
5. Ability to work independently, prioritise competing requirements and deliver solutions in a fast-paced environment.
6. Strong interest in financial markets and willingness to develop knowledge across trading, risk and quantitative workflows.
7. Comfortable using AI-assisted development tools to improve productivity and accelerate software delivery.

1. Experience developing applications within financial markets, trading desks, hedge funds, asset management or investment banking environments.
2. Understanding of quantitative finance concepts, including:
3. Interest rates and fixed income products
4. Options and volatility
5. Risk analytics and VaR
6. Pricing methodologies
7. Portfolio analytics
8. Experience working with SQL and relational databases.
9. Exposure to quantitative libraries or financial modelling frameworks.
10. Experience with cloud technologies and infrastructure.
11. Familiarity with monitoring and observability tools.
12. Bloomberg Terminal experience is advantageous.
13. Previous experience using AI coding assistants such as Claude Code, Cursor, Copilot or similar tools.

1. Direct Front Office Exposure – Work closely with Portfolio Managers, Traders, Quants and Risk teams with direct visibility into investment and trading workflows.
2. High Ownership Environment – Take responsibility from understanding business requirements through design, development and delivery.
3. Broad Technology Exposure – Work across quantitative analytics, trading applications, risk systems, market data and investment workflows.
4. Not a Traditional Software Engineering Role – Success requires understanding the business problem, designing the right solution and delivering technology that creates value for investment teams.
5. AI-Enabled Development Environment – Use modern AI development tools to improve delivery speed while applying strong engineering judgement and architectural thinking.