C++ Software Developer

C++ Software Developer, Risk Technology

£180,000 to £200,000

Join a specialist engineering team responsible for the technology that underpins a global trading risk platform. This environment sits at the intersection of quantitative research, front office trading, and high-performance engineering, where systems must process enormous volumes of market and trade data while maintaining absolute accuracy of risk calculations across multiple asset classes. The platform ingests trades in real time, tracks positions across portfolios, calculates PnL and exposures, and distributes risk metrics across internal systems used by trading and portfolio management teams.

We are looking for a C++ engineer who understands the technology challenges associated with financial risk systems. You will be working on software that models complex financial instruments and asset classes, ensuring that risk calculations remain consistent, deterministic, and performant as trading activity and data volumes increase. Engineers here regularly deal with issues such as market data ingestion, pricing model integration, portfolio aggregation, and the propagation of risk metrics across distributed systems used by the front office.

The architecture is evolving toward a service-oriented model designed to support large scale distributed compute across a Linux estate. You will help build components that process high frequency data flows, maintain state across complex portfolios, and deliver reliable risk analytics under strict latency constraints. This is a role for engineers who enjoy understanding both the technical and financial dimensions of a system, translating trading concepts into efficient and maintainable software.

What you bring

• Strong C++ development experience within Linux environments

• Prior experience building systems in financial services, ideally within trading or risk platforms

• Exposure to financial asset classes such as equities, derivatives, FX, or fixed income and an understanding of how risk is calculated across them

• Deep knowledge of algorithms, memory management, multithreading and performance optimisation

• Experience working with large scale distributed systems and high volume market or trade data

• Familiarity with messaging technologies such as Kafka, AMPS or QPID

• Python or bash for tooling and automation, with exposure to Q or KDB considered valuable

If you enjoy solving challenging engineering problems at the heart of trading technology and want to build systems that directly support risk and portfolio management across complex financial instruments, Ncounter would welcome a conversation.