Software Development Manager

3 days ago


Mumbai, Maharashtra, India Clearwater Analytics Full time US$ 1,50,000 - US$ 2,00,000 per year

Clearwater Analytics' mission is to become the world's most trusted and comprehensive technology platform for investment reporting, accounting, and analytics.  With our team, you will partner with the most sophisticated and innovative institutional investors around the world. If you are infectiously passionate about what you do, intensely committed to clients, and driven by continuous innovation and improvement... We want you to apply

You will ensure team processes are understood, followed, and improved. Responsible for developing and evaluating personnel to ensure efficient operation, continued growth, and positive employee engagement. Responsible for ensuring the delivery of business goals assigned to the team. 
 

Desired Experience and Skills

Lead Quantitative Developer – Risk Platform Infrastructure

Beacon Platform by CWAN builds a cloud-based development environment that enables quants, data scientists, and commercial developers to rapidly build and deploy the functionality their businesses need at the largest scales. Additionally, we build and externalize trading and risk management applications for all sides of the financial services industry.

We are looking for a Lead Quantitative Developer to architect and oversee the development of highly reliable and scalable risk infrastructure that supports front-office decision-making across asset classes—including 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.

You will lead a small team of quants responsible for delivering and maintaining the quantitative backbone of our platform. This includes model calibration pipelines, EOD risk jobs, lifecycle management, regression testing, and configurable modeling workflows—all designed for performance, reliability, and extensibility in a front-office environment.

What You'll 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.

  • Lead and mentor a team of quantitative developers focused on delivering production-quality, client-facing analytics.

  • 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

  • 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 environments—especially 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.



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