Fixed Income Quantitative Developer

About Vichara

Vichara is a global leader in enterprise systems and quantitative solutions for institutional capital-markets participants. Our platforms manage billions in fixed-income assets, powering valuation, risk, accounting, and data workflows for leading investment firms worldwide. Headquartered in New Jersey, we operate major development centers in Gurgaon, Toronto, and Bogotá. Learn more at www.vichara.com.

Role Overview

We are partnering with a top-tier asset manager that is replacing its third-party analytics stack with a

next-generation, open-source valuation and risk platform . As part of our quantitative development team, you will play a key role in building this greenfield solution using

Python and C++ , leveraging

QuantLib

and the

Open-Source Risk Engine (ORE) .

You will work on model development, system integration, and performance optimization, while validating results against legacy analytics and delivering a scalable solution for complex fixed-income portfolios covering sovereigns, corporates, MBS / ABS, and derivatives.

What You’ll Do

Architect and implement

pricing, curve-building, cash-flow, and risk components

using QuantLib / ORE, with Python bindings for desk-level analytics.

Develop and calibrate

term-structure, credit-spread, and volatility models

(e.g., Hull-White, SABR, HJM) in C++ with robust Python wrappers.

Enhance performance through

multithreading, caching, and optimization techniques .

Integrate external market data and build seamless workflows.

Contribute to infrastructure setup with

Azure Kubernetes , CI / CD automation, and Git-driven collaboration.

What We’re Looking For

Master’s / PhD in

Quantitative Finance, Financial Engineering, or a related field .

5+ years of experience

in building pricing or risk libraries for rates or credit products.

Hands-on exposure to

FinCAD, or in-house risk / pricing libraries

is an advantage.

Strong programming skills in

C++

(for high-performance computing) and / or

Python .

Proven expertise with

QuantLib

(open-source contributions highly valued) and familiarity with

ORE architecture .

Solid understanding of

curve construction, bootstrapping, Monte Carlo simulations, PDE methods, and XVA frameworks .

Practical knowledge of

cloud-native tools : Azure CI pipelines, Docker / Kubernetes, and collaborative Git workflows.