As a Lead Software Engineer at JPMorgan Chase within the Athena Engineering team, you will design, build, and enhance backend services and capabilities within the Athena ecosystem to support an externally facing cross-asset risk platform (FX, Rates, Credit, Equities).
This solution is a feature rich platform, offering traders and investment managers top-tier tools to optimize their portfolios and reduce risk exposure in a high-performance, externally facing client environment.
Job Responsibilities:
1. Athena Engineer (Back End): design, build, and enhance backend services and capabilities within the Athena ecosystem to support an externally facing cross-asset risk platform (FX, Rates, Credit, Equities).
2. Build out new functions in risk management applications using Python for the backend and React, Redux, and TypeScript for the frontend.
3. Collaborate with engineers and product management across the globe to deliver high-quality solutions for external clients.
4. Build out the service layer monitoring and control functionality, maximizing the platform resiliency and robustness in a high-availability, high-throughput environment.
5. Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
6. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Required qualifications, capabilities and skills
7. Seasoned developer experienced in high level languages such as: Python, C++, Java, or JavaScript.
8. Proactive and independent — able to take ownership of deliverables and solve real world business problems in a client-facing production environment.
9. Strong analytical and problem-solving skills.
10. Demonstrated experience leading effective use of approved AI-assisted software development tools (., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
11. Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
12. Excellent verbal and written communication skills.
Preferred qualifications, capabilities and skills
13. Experience in Python (backend).
14. Experience in React and TypeScript.
15. Experience in finance / investment banking as an application developer, ideally with exposure to FX, Rates, Credit, and/or Equities.
16. Experience building and supporting high-performance backend systems (., low-latency services, high-throughput APIs, observability/monitoring, resiliency patterns).