Quantitative Developer

Quantitative Developer Risk Platform Infrastructure

Location:- Mumbai

We are looking for Quantitative Developer to architect and oversee the development of highly reliable and scalable risk infrastructure that supports front-office decision-making across asset classesincluding equities, commodities, fixed income, and FX. This role is ideal for candidates who are passionate about building robust systems that deliver accurate pricing, risk, and analytics under production constraints.

What Youll Do

• Own the architecture, design, and delivery of the quant infrastructure powering front-office risk and analytics.
• Build scalable frameworks for valuation, risk, scenario analysis, and lifecycle modeling across multiple asset classes.
• Ensure platform reliability through robust EOD processing pipelines, model calibration workflows, and automated regression testing.
• Implement standards for versioning, model governance, and platform health monitoring to ensure system integrity over time.
• Design flexible infrastructure to support client-specific configurations without compromising performance or maintainability.
• Collaborate with engineering and product teams to align platform design with business and technical requirements.

What We Are Looking For

• 3 - 5 years of experience in quantitative development or financial engineering with broad asset class exposure.
• Strong engineering mindset with a focus on system reliability, maintainability, and performance.
• Expertise in Python and familiarity with modern software development practices (CI/CD, testing, observability).
• Experience building and operating quantitative infrastructure in production environmentsespecially for pricing and risk analytics.
• Proven ability to lead and grow technical teams.
• Strong understanding of trade lifecycle modeling, model calibration, and data orchestration in a risk platform context.

What Will Make You Stand Out

• Track record of delivering and operating robust quant systems at scale in a front-office or risk platform environment.
• Experience designing systems for automated recovery, failover, and monitoring of analytics jobs.
• Familiarity with distributed computing, EOD risk workflows, and large-scale job orchestration (e.g., Airflow, Prefect).
• Prior experience integrating complex model libraries into production platforms while maintaining reliability and transparency.