Support existing trader-facing live risk and PnL applications in production, including day-to-day health, stability, and responsiveness to desk needsTroubleshoot and resolve issues efficiently across the stack (data, calculations, services, infrastructure dependencies), performing root-cause analysis and implementing durable fixesWork closely with Rates traders and stakeholders to gather requirements and translate them into high-quality, low-latency technical solutionsDevelop and deliver enhancements to live risk and PnL functionality with strong engineering discipline (testing, code quality, performance, secure coding, operational readiness)Deliver critical Rates risk and PnL projects, coordinating with partner teams to deliver under tight timelines and high business impactImprove monitoring, alerting, and operational runbooks; participate in incident management and post-incident remediation as neededContinuously identify and address technical debt, performance bottlenecks, and data quality gaps to improve resiliency and user experienceDrives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., 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.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
Hands-on experience in system design, application development, testing, and operational stability with a track record of leading complex technical initiativesStrong front-office experience supporting trading (direct engagement with traders, rapid iteration, production ownership)Strong Rates product and business knowledge (Rates trading workflows, market data, risk, PnL, trade lifecycle)Advanced proficiency in Python, including building production services and performance-sensitive applicationsStrong 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 responseProven ability to lead technical design discussions, mentor engineers, and partner effectively with business stakeholdersStrong problem-solving skills and ability to learn quickly and deliver high-quality outcomes under time pressureDemonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.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