As a Lead Software Engineer at JPMorganChase within Global Technology, you will lead and mentor an agile team to architect, design, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. In this role on the Rates Live Risk & PnL team, you will build and operate low-latency, high-availability Python applications used directly by Rates trading desks for intraday risk, PnL, and decision support in a fast-paced, front-office environment.
The Rates Live Risk & PnL team delivers real-time trading risk and profit & loss capabilities, partnering closely with traders and desk strategists. You will own critical components across the stack—from data ingestion and calculation services to UI and operational tooling—ensuring performance, correctness, and resiliency under tight timelines and high business impact.
Job Responsibilities
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience in coding Java or Python, including building production services and performance-sensitive applications
- Financial markets background (Rates products, risk, PnL, market data, trade lifecycle)
- Hands-on experience in system design, application development, testing, and operational stability with a track record of leading complex technical initiatives
- Strong understanding of real-time/distributed system concepts (e.g., concurrency, messaging/streaming patterns, caching, failure modes)
- Experience delivering software in a large corporate environment with strong engineering standards (testing, code quality, security, SDLC)
- Practical experience with CI/CD, application resiliency, and secure engineering, including production monitoring and incident response
- Proven ability to lead technical design discussions, mentor engineers, and partner effectively with business stakeholders
- Strong problem-solving skills and ability to learn quickly and deliver high-quality outcomes under time pressure
Preferred qualifications, capabilities, and skills
- Exposure to Deephaven (or similar real-time analytics/UI platforms) and its ecosystem, including installation/runtime dependencies (e.g., Java) and related operational considerations
- Experience with DevOps practices for low-latency services (deployments, observability, capacity/performance testing, environment management)
- Understanding of UI programming (web or desktop) and collaborating across UI/backend boundaries to deliver trader-facing workflows
- Familiarity with Java and/or mixed-language environments where Python services interact with JVM-based components
- Experience with event-driven architectures and high-performance data pipelines used in front-office systems