Quant Dev Manager

Location: Gurugram, Haryana, India

Department: Weekday's Client via platform

Workplace: on_site

Employment Type: full

Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟲𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟱𝟬-𝟲𝟬 𝗟𝗣𝗔)

Experience: 4+ yrs

Location: Gurugram, Haryana, India, Gurgaon, Haryana, India

Job Type: Full-time

We are seeking a highly skilled Risk Engine Developer 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 modern C++ 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 modern C++ (C++17/20/23) 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 modern C++ and Python.
• Strong expertise in distributed systems, parallel computing, multithreading, asynchronous programming, and performance optimization.
• Experience building Risk Engines, Pricing Engines, Analytics Platforms, Quantitative Libraries, or High-Performance Computing (HPC) 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.