Senior Python Engineer - AI-Driven Risk & PnL

Fairygodboss; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

J.P. Morgan is seeking a Senior Python Developer to join the Athena Rates team, delivering risk and PnL solutions for rates products. You will design, develop, and integrate scalable software for trading desks and back offices, interfacing across middle and back office systems.

The role requires 5+ years Python experience, strong software engineering fundamentals, and collaboration with quants, traders, and risk managers to implement robust data pipelines and analytics.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied Python experience
• Bachelor's degree in CS or equivalent
• Solid understanding of OOP, testing, and version control practices
• Demonstrated ability to write clean, maintainable code in large codebases
• Strong communication skills for cross-team collaboration

Responsibilities

• Develop scalable, performant code for market data and calculations including risk metrics and PnL attribution
• Participate in architectural decisions, code reviews, and design sessions
• Drive AI-assisted engineering practices to improve quality, speed, and automation while ensuring secure coding and testing standards
• Apply SDLC tools to improve automation and value realization across the team

Skills

Python

Finance domain knowledge

Software architecture

Code reviews

AI-assisted development

Education

Bachelor's degree in Computer Science or equivalent

Tools

CI/CD pipelines

Docker

Kubernetes

SQL/NoSQL databases

Job description

J.P. Morgan is seeking a Senior Python Developer to join the Athena Rates team, delivering risk and PnL solutions for rates products. You will design, develop, and integrate scalable software for trading desks and back offices, interfacing across middle and back office systems.

The role requires 5+ years Python experience, strong software engineering fundamentals, and collaboration with quants, traders, and risk managers to implement robust data pipelines and analytics.