Qaunt developer

Design, develop, and maintain Murex Flex components using C++
Integrate proprietary Quant pricing and risk libraries into Murex via Flex APIs
Partner closely with Quant teams to understand model assumptions, limitations, and implementation requirements
Ensure robust interaction between Murex core, Flex extensions, and external Quant libraries
Support complex Front Office use cases including pricing, Greeks, sensitivities, and payoffs
Participate in UAT, model validation support, and production releases, including controlled rollout of changes
Diagnose and resolve production issues related to Flex, pricing behavior, or model integration
Contribute to platform stability, performance optimization, and risk reduction
Work with QA, Release Management, and Production Support to ensure functional correctness and operational readiness
Adhere to governance, change management, and Front Office risk controls

Interaction Model
Daily collaboration with EQD Quant teams on model integration and enhancements
Regular interaction with Front Office Technology stakeholders
Close coordination with QA, Release, and Production Support teams
Engagement with external vendors (e.g., Murex) as required for model or platform changes

Strong, hands on C++ development experience in a production environment
Experience integrating Quant or pricing libraries into trading or risk platforms
Ability to work directly with Quants and translate quantitative concepts into robust C++ implementations
Strong debugging and troubleshooting skills in Linux/Unix environments
Experience supporting UAT and production environments in Front Office systems
Strong understanding of software quality, performance, and stability in risk sensitive platforms

Exposure to Python (for prototyping, tooling, or Quant collaboration)
Strong knowledge of Equity Derivatives, particularly autocalls and structured products
Understanding of pricing models, Greeks, sensitivities, and risk calculations
Experience with Murex Flex (Flex libraries, APIs, integration patterns)
Experience with performance sensitive or numerically intensive systems
Exposure to GPU programming (CUDA, OpenCL, or similar) for computational acceleration