Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase within the Commodities Transformation Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
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Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
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Develops next-gen applications for Commodities trading desks across the globe at JPMorganChase
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Develops secure and high-quality production code, and reviews and debugs code written by others
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Liaises with users such as Product and Financial Controllers to understand reporting needs, and investigates and resolves reporting issues
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Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain
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Leverages agentic development pipelines to build solutions and accelerate delivery
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Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale
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Drives decisions that influence the product design, application functionality, and technical operations and processes
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Serves as a function-wide subject matter expert in one or more areas of focus
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Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
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Formal training or certification on software engineering concepts and advanced applied experience
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Experience working with Front Office Trading Desks
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High proficiency in Python
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Strong problem-solving skills, with the ability to diagnose and resolve complex reporting and system issues
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Proven ability to liaise with business users such as Product and Financial Controllers to elicit reporting requirements and translate them into technical solutions
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Solid understanding of Risk and PnL reporting infrastructure paradigms and systems
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Hands-on practical experience delivering system design, application development, testing, and operational stability
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Advanced in one or more programming language(s)
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Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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
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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 senior engineers/leads on compliant usage patterns and controls
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Experience using agentic development pipelines to build and deliver solutions
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Ability to tackle design and functionality problems independently with little to no oversight
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Practical cloud native experience
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Hands-on experience developing on the Athena platform or a comparable Python risk management platform
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Domain knowledge of Commodities products and derisking workflows
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Experience building or integrating Risk and PnL reporting infrastructure in a Front Office environment
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Familiarity with agentic AI development pipelines and their application to production engineering
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Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security