As a Senior Lead Software Engineer at JPMorganChase within theCommercial & Investment Technology in Cash Prime Technology, youare 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm27s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications Drive the delivery of business value via change programs, projects within the technology group
• Create automated unit tests using a Test Driven Development approach
• Develop a strong understanding of key functions of clearing and settlements within Cash Prime business
• Partner with supporting tech leads to develop realistic and achievable project estimates.
• Analyze and build within Control, Stability, Resiliency, Capacity & Performance areas.
• Perform testing: Unit, SIT & UAT planning and management.
• Doing robust delivery of code into the production environment with zero tolerance for post implementation issues
• Take part in decisions affecting long range organizational goals & strategic planning. Proactively look to develop, implement and further development best practices and contribute to quality improvement, code reviews, code and architecture standards, code reuse etc.
• 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.
• 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.

Required qualifications, capabilities, and skills

• Formal degree or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Strong core Java experience with clear understanding of advanced concepts in collection framework, garbage collection, multi-threading etc.
• Hands on experience in Java\J2EE,Spring Boot, Database knowledge,Kafka, React JS, CI\CD, designing features, AWS cloud experience
• Strong problem solving, analytical and communication skills (both verbal and written)
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
• Ability to take on difficult and complex large scale problems and provide end to end solutions.
• Ability to build and maintain strong relationships with stakeholders in business, operations, operate etc.
• 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
• 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.
• Designing & developing micro-front end based micro-services.
• Exposure to Kubernetes platform
• Exposure to DevOps methodology

Preferred qualifications, capabilities, and skills

• Designing & developing micro-front end based micro-services.
• Exposure to Kubernetes platform
• Exposure to DevOps methodology