Software Engineer

We are seeking a highly talented and driven Python Front Office Developer to join our fast-paced trading technology team. In this role, you will sit directly on the trading floor, collaborating closely with traders, quantitative analysts, and risk managers. You will be responsible for designing, building, and maintaining business-critical applications that drive intraday decision-making, real-time risk evaluation, pricing models, and trade execution management., * Trading Desk Systems Development: Design, develop, and optimize high-performance, real-time Python applications and APIs supporting automated trading, market data feeds, and pricing engines. [

• Risk & P&L Platforms: Build and support systems that handle intraday and end-of-day risk calculations, Profit and Loss (P&L) explanations, and secondary market booking workflows
• Rapid Prototyping: Partner directly with quantitative researchers and traders to turn mathematical models and tactical requirements into stable, functional production software.
• Data Engineering & Analytics: Build and maintain scalable, transversal data platforms using scientific Python libraries to accelerate data analysis and visualization across the firm.
• DevOps & Infrastructure: Manage and automate modern CI/CD pipelines utilizing containerization technologies to ensure frictionless deployment and high availability of live environments.
• System Optimization: Identify performance bottlenecks in latency-critical code, refactoring and optimizing logic to ensure flawless secondary market activities.

For a complete understanding of this opportunity, and what will be required to be a successful applicant, read on.

• The ideal candidate possesses exceptional core Python programming skills alongside a deep, functional understanding of capital markets and trade lifecycles., * Experience: Minimum of 2+ years explicitly focused on Python backend or full-stack software development.
• Core Python Expertise: Advanced proficiency in modern object-oriented Python, including data-centric and scientific libraries such as Pandas, NumPy, and SciPy.
• Domain Knowledge (Mandatory): Solid understanding of Capital Markets and asset classes (e.g., Fixed Income, Equity Derivatives, Commodities, or FX) alongside Order Management Systems (OMS) or Execution Management Systems (EMS). xrbllit
• Database & SQL: Extensive experience handling large financial datasets utilizing SQL, relational databases, or time-series databases.