Quantitative Technology Developer - Python and C++ - Vice President

Citi; Pune District; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Citi is seeking a Senior Quantitative Technology Developer for the Analytical Calculation Engine (ACE) in Pune. You will design and extend the strategic analytics platform powering derivatives credit risk, pricing, and exposure calculations across asset classes.

Collaborate with Quantitative Research and Model Development to implement pricing models and optimize performance. You will contribute to automated testing, CI/CD pipelines, and environment management, while mentoring junior engineers

Qualifications

• Bachelor’s or Master’s in CS/Engineering/Math/Financial Engineering or related quantitative field.
• Strong software engineering experience in Capital Markets, Risk Tech, or Financial Services.
• Expert-level Python for production-grade analytics and libraries.

Responsibilities

• Design, develop, and maintain strategic risk analytics applications for derivatives credit risk and exposure.
• Develop, enhance, and support quantitative technology solutions with in-house Python and C++ libraries.
• Collaborate with Quantitative Research, Model Development, and Front Office Tech to integrate pricing models into ACE.
• Design scalable, high-performance calculation workflows across asset classes.
• Analyze and optimize performance, memory usage, and efficiency of large-scale risk calculations.
• Develop and extend automated testing frameworks (unit, regression, integration, performance).

Skills

Python

C++

Linux

Git

CI/CD

Testing

Analytical thinking

Communication

Education

Bachelor's or Master's degree in Computer Science / Engineering / Mathematics / Financial Engineering

Tools

Git

Jenkins

CI/CD pipelines

Linux/Unix shell

Job description

The Opportunity

The Analytical Calculation Engine (ACE) Development Team is responsible for building and maintaining Citi's strategic platform for derivatives credit risk and exposure calculations. The platform supports critical risk management, regulatory capital, and risk analytics functions across the firm and serves as a cornerstone of Citi's Financial Risk Technology landscape. We are seeking a hands-on Senior Quantitative Technology Developer to join the ACE team and contribute to the development of high-performance risk analytics solutions. This role offers a unique opportunity to work at the intersection of quantitative finance, software engineering, and large-scale distributed computation while partnering closely with Quantitative Research, Model Development, Risk Management, and Front Office Technology teams.

Your Role and Impact

As a member of the ACE development team, you will design, develop, and enhance the strategic analytics platform that powers derivatives credit risk calculations across multiple asset classes. You will collaborate with quantitative analysts, model developers, and technology teams to implement pricing and exposure models, improve computational efficiency, and deliver robust risk analytics solutions used across the firm. This role combines strong software engineering skills with an understanding of quantitative modeling and risk management. You will contribute to strategic platform initiatives, application modernization efforts, and the delivery of key business and regulatory capabilities.

Key Responsibilities

• Design, develop, and maintain strategic risk analytics applications supporting derivatives credit risk and exposure calculations.
• Develop, enhance, and support quantitative technology solutions leveraging in-house Python and C++ analytics libraries.
• Partner with Quantitative Research, Model Development, and Front Office Technology teams to integrate pricing models and analytical enhancements into the ACE platform.
• Contribute to the design and implementation of scalable, resilient, and high-performance calculation workflows spanning multiple asset classes.
• Analyze and optimize computational performance, memory utilization, and processing efficiency of large-scale risk calculations.
• Develop and extend automated testing frameworks, including unit, regression, integration, and performance testing.
• Support software release processes, CI/CD pipelines, and environment management activities.
• Investigate and resolve complex production, performance, and analytical issues.
• Collaborate with stakeholders across Risk, Quantitative Analytics, and Technology organizations to deliver business and regulatory priorities.
• Produce high-quality technical documentation and contribute to development standards and engineering best practices.
• Mentor junior developers and contribute to a collaborative, high-performing engineering culture.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Financial Engineering, or a related quantitative discipline.
• Strong software engineering experience within Capital Markets, Risk Technology, Quantitative Analytics, or Financial Services environments.
• Expert-level Python programming skills with experience building production-grade applications and analytics frameworks.
• Strong C++ development experience, with an emphasis on performance, scalability, and maintainability.
• Experience developing and supporting analytics libraries for derivatives pricing, exposure calculations, or risk management platforms.
• Strong understanding of object-oriented design, software architecture, data structures, and algorithms.
• Experience developing software on Linux/Unix platforms.
• Familiarity with SDLC processes, Git, Jenkins, CI/CD pipelines, and automated testing frameworks.
• Strong analytical and problem-solving skills with attention to detail and quality.
• Excellent communication and collaboration skills, with the ability to work effectively across global teams.
• Proven ability to take ownership of complex deliverables and drive them to successful completion.

Preferred Qualifications

• Knowledge of Counterparty Credit Risk (CCR), Exposure Modeling, XVA, Market Risk, or quantitative risk analytics.
• Understanding of derivatives products across Rates, Credit, Equities, FX, and Commodities asset classes.
• Familiarity with numerical methods, statistical analysis, optimization techniques, and Monte Carlo simulations.
• Experience working on regulatory initiatives including Basel, Stress Testing, FRTB, CCAR, or Model Risk Management.
• Exposure to distributed computing, high-performance computing, or large-scale analytics platforms.
• Prior experience working closely with quantitative researchers and model development teams.

Time Type

Full time

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