Job Description For Risk Engine Developer
What You'll Do
You'll help design, build, and evolve the Bank's strategic Risk Engine, the core computational platform powering risk calculations across all asset classes. This platform is relied upon daily by Trading Desks, Risk Managers, and Quantitative teams to produce critical risk measures, including risk sensitivities, Delta ladders, VaR inputs, FRTB-SA sensitivities, stress-testing metrics, and PnL Explain.
Working closely with Quants, Trading Desks, and Engineering teams in London, you will develop and enhance a highly scalable distributed compute platform capable of processing millions of valuations and risk calculations across the Bank's global portfolios. The role requires a strong focus on modern C++, distributed computing, performance optimization, and large-scale numerical analytics.
Key Responsibilities
Design and develop high-performance applications using modern C++ (C++17/20/23) and Python.
Contribute to the Bank's strategic Risk Engine Grid, a large-scale distributed computation platform responsible for risk calculations across Rates, Credit, FX, Equities, Commodities, and Structured Products.
Develop scalable distributed solutions capable of processing millions of trades and large volumes of market data across enterprise-wide grid infrastructure.
Design and implement parallel and distributed computation frameworks for valuation, sensitivities, stress testing, and regulatory risk calculations.
Optimize computationally intensive workloads for latency, throughput, memory efficiency, and horizontal scalability.
Build resilient, production-grade systems that operate at enterprise scale and support time-critical risk management processes.
Develop and enhance risk analytics including Delta, Vega, Curve Sensitivities, VaR inputs, PnL Explain, and Risk Attribution capabilities.
Collaborate with Quantitative Analysts and Trading Desks to productionize new analytics and model.
Contribute to the architecture and development of strategic C++ and Python libraries, ensuring maintainability, consistency, and performance.
Drive engineering excellence through automated testing, CI/CD, code reviews, observability, and software design best practices.
Preferred Experience
Strong experience developing large-scale applications using modern C++.
Experience building or enhancing Risk Engines, Pricing Engines, Analytics Platforms, or Quantitative Libraries.
Strong understanding of concurrency, multithreading, asynchronous programming, and distributed systems.
Experience with large-scale distributed compute platforms, grid computing, or high-performance computing (HPC) environments.
Experience developing frameworks for valuation, risk sensitivities, VaR, stress testing, xVA, or other quantitative analytics.
Strong understanding of performance profiling, optimization, memory management, and low-latency design principles.
Knowledge of Fixed Income, Interest Rate Derivatives, FX, Credit, Equities, Commodities, or Structured Products is advantageous.
Experience working in Linux environments and modern software development practices, including Git, CI/CD, and automated testing.
Ideal Candidate
We're looking for a highly motivated engineer who enjoys solving complex computational problems at scale and has a passion for building high-performance software.
The ideal candidate will have a proven track record of developing high-performance C++ systems, distributed computing platforms, quantitative analytics frameworks, risk engines, or pricing libraries. Experience in performance-critical environments, large-scale numerical computation, and parallel processing will be highly valued.
This role offers the opportunity to work on a strategic Risk Engine Grid, a mission-critical platform that powers risk calculations across all asset classes within the Bank. You will be tackling some of the most challenging problems in distributed computation, quantitative analytics, and performance engineering while delivering solutions that directly support trading and risk management activities globally.
