Python Lead Software Engineer - Rates Risk & P&L

Description

You will join a front-office engineering team that builds and operates core Rates trading tooling where correctness, resilience, and latency matter every day. The environment is fast-moving and highly collaborative, with strong expectations for production ownership, rapid iteration, and high-quality delivery.

• Build and enhance Python services and applications that power live Rates risk and P&L, with a strong focus on low latency and predictable performance.
• Partner directly with traders and risk managers to turn time-sensitive requirements into reliable, production-ready solutions.
• Own production services end-to-end, including releases, monitoring, incident response, and root-cause analysis.
• Troubleshoot issues across distributed components, data flows, and runtime environments; drive fixes that reduce recurrence.
• Improve Dev Ops and operational readiness, including CI/CD, environment management, dependency management, and automation.
• Maintain strong engineering standards through code reviews, testing discipline, performance profiling, and clear documentation/runbooks.

• Strong Python development skills, including writing production-quality code with solid testing and packaging practices.
• Experience building and operating production services, including production support and incident-driven troubleshooting.
• Practical SDLC discipline across design, implementation, testing, deployment, and release management.
• Experience with CI/CD and observability (monitoring, alerting, logs/metrics) to keep services stable and measurable.
• Ability to work closely with front-office stakeholders and deliver effectively when priorities shift.
• Strong debugging skills and comfort navigating multi-component systems.

• Financial markets background, especially Rates trading, risk, or P&L concepts.
• Exposure to Deephaven, including installation and dependencies (for example GKP, Java interoperability, and runtime operations).
• Low-latency/performance engineering experience (profiling, concurrency, and latency measurement).
• Understanding of UI programming and interactive workflows used by traders.
• Strong Dev Ops mindset (automation, environment consistency, and operational ownership).