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About the role
As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Banks Credit Technology team, you have an exciting opportunity to work on real-time and end-of-day Risk & PnL platforms for Bonds, Loans, Credit Derivatives, Exotics products, and more. Your role involves designing and delivering secure, resilient, low-latency, and scalable services to support front-office risk, trading, and management reporting workflows. You will collaborate with quant, trading, risk, and production management teams to drive technical delivery and engineering standards. Key Responsibilities: - Build real-time Risk/PnL systems for various financial products, such as Loans, Credit Derivatives, and Exotics products, including intraday Greeks/sensitivities, VaR inputs, explain/attribution, scenario and stress runs. - Design and deliver low-latency, high-throughput services with clear SLAs, observability, and operational readiness for front-office consumers. - Develop distributed microservices and event-driven pipelines to consume market data, trades, and reference data, produce risk measures, and serve APIs/UI consumers. - Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes. - Apply strong engineering rigor in test strategy, performance profiling, capacity planning, resiliency patterns, and secure coding. - Collaborate with stakeholders to translate business needs into technical requirements and deliver iteratively. - Mentor engineers, contribute to code reviews, raise the bar on architecture and craftsmanship, and foster an inclusive team culture. Qualification Required: - Formal training or certification on software engineering concepts and 12+ years of applied experience. - Extensive hands-on experience delivering Python services in production, including design, development, testing, troubleshooting, and operational support. - Strong knowledge of data structures, algorithms, concurrency, and software design principles. - Experience across the full Software Development Life Cycle (SDLC), including CI/CD, testing automation, release management, and production support. - Strong SQL skills and experience with relational databases, including schema design and writing performant queries. - Proven ability to build secure, stable, maintainable systems in a large enterprise environment. - Demonstrated experience leading the effective use of approved AI-assisted software development tools. - Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs/outputs. - Experience building real-time systems, proficiency with profiling and performance tuning, and designing for throughput and backpressure. You will play a crucial role in the development and maintenance of cutting-edge risk and PnL platforms while contributing to a culture of technical excellence and innovation at JPMorgan Chase. As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Banks Credit Technology team, you have an exciting opportunity to work on real-time and end-of-day Risk & PnL platforms for Bonds, Loans, Credit Derivatives, Exotics products, and more. Your role involves designing and delivering secure, resilient, low-latency, and scalable services to support front-office risk, trading, and management reporting workflows. You will collaborate with quant, trading, risk, and production management teams to drive technical delivery and engineering standards. Key Responsibilities: - Build real-time Risk/PnL systems for various financial products, such as Loans, Credit Derivatives, and Exotics products, including intraday Greeks/sensitivities, VaR inputs, explain/attribution, scenario and stress runs. - Design and deliver low-latency, high-throughput services with clear SLAs, observability, and operational readiness for front-office consumers. - Develop distributed microservices and event-driven pipelines to consume market data, trades, and reference data, produce risk measures, and serve APIs/UI consumers. - Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes. - Apply strong engineering rigor in test strategy, performance profiling, capacity planning, resiliency patterns, and secure coding. - Collaborate with stakeholders to translate business needs into technical requirements and deliver iteratively. - Mentor engineers, contribute to code reviews, raise the bar on architecture and craftsmanship, and foster an inclusive team culture. Qualification Required: - Formal training or certification on software engineering concepts and 12+ years of applied experience. - Extensive hands-on experience delivering Python services in production, including design, development, testing, troubleshooting, and operational support. - Strong knowledge of data struct
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