๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฒ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฑ๐ฌ-๐ฒ๐ฌ ๐๐ฃ๐)
Experience: 4+ yrs
Location: Gurugram, Haryana, India, Gurgaon, Haryana, India
Job Type: Full-time
We are seeking a highly skilledย Risk Engine Developerย to design, develop, and optimize a strategic enterprise Risk Engine that powers large-scale risk analytics across multiple asset classes. This role is ideal for professionals who are passionate about high-performance computing, distributed systems, and quantitative engineering, with strong expertise in modernย C++ย and scalable software architecture.
As a Risk Engine Developer, you will collaborate closely with Quantitative Analysts, Trading teams, Risk Managers, and Engineering teams to build highly scalable computational platforms capable of processing millions of valuations, market data events, and risk calculations. You will play a key role in delivering high-performance risk analytics, improving distributed compute frameworks, and enabling mission-critical trading and risk management capabilities through innovative engineering solutions.
Requirements
Key Responsibilities
- Design, develop, and maintain high-performance applications using modernย C++ (C++17/20/23)ย and Python.
- Build and enhance scalable distributed computation platforms for enterprise-wide risk calculations and quantitative analytics.
- Develop frameworks for valuation, pricing, sensitivities, stress testing, Value at Risk (VaR), and regulatory risk calculations.
- Design distributed and parallel computing solutions capable of processing large-scale market data and complex financial portfolios.
- Optimize application performance for latency, throughput, scalability, memory utilization, and computational efficiency.
- Develop resilient, production-grade software supporting high-volume, time-critical risk management processes.
- Implement and enhance quantitative analytics, including Delta, Vega, Curve Sensitivities, PnL Explain, Risk Attribution, and related calculations.
- Collaborate with Quantitative Analysts and business stakeholders to productionize new analytical models and computational capabilities.
- Contribute to reusable C++ and Python libraries while promoting maintainable architecture, clean code, and engineering best practices.
- Participate in architecture discussions, code reviews, automated testing, CI/CD implementation, and continuous platform improvements.
- Monitor, troubleshoot, and optimize distributed computing environments to ensure operational reliability and performance.
What Makes You a Great Fit
- 4+ years of experience developing high-performance software using modernย C++ย and Python.
- Strong expertise in distributed systems, parallel computing, multithreading, asynchronous programming, and performance optimization.
- Experience buildingย Risk Engines, Pricing Engines, Analytics Platforms, Quantitative Libraries, or High-Performance Computing (HPC)ย solutions.
- Strong understanding of large-scale distributed compute platforms, grid computing, and enterprise-scale computational architectures.
- Experience developing quantitative analytics including valuation models, sensitivities, VaR, stress testing, xVA, or related financial calculations.
- Solid knowledge of performance profiling, memory management, low-latency system design, and scalable software engineering principles.
- Familiarity with Fixed Income, Interest Rate Derivatives, FX, Credit, Equities, Commodities, Structured Products, or financial risk management concepts is an advantage.
- Experience working in Linux environments with Git, CI/CD pipelines, automated testing, and modern DevOps practices.
- Strong analytical, debugging, and problem-solving skills with the ability to solve complex computational challenges.
- Excellent collaboration and communication skills, with the ability to work effectively alongside quantitative, engineering, and business teams in a fast-paced environment.