Lead Software Engineer - Fullstack

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 Lead Software Engineer at JPMorganChase within the Global Finance Technology, 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: Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices. Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution. Develops secure high-quality production code, and reviews and debugs code written by others. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems. 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. Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Promptly investigate and resolve issues, ensuring they do not resurface. Continuously update technologies and patterns to keep systems current. Design and build solutions that avoid single points of failure using scalable architectural patterns. Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance. Required qualifications, capabilities, and skills: Formal training or certification on software engineering concepts and 5+ years of hands-on experience in software engineering, including system design, application development, testing, and operational support. Proficiency in back-end technologies (e.g., Python, Flask, Django) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular). Demonstrated ability to independently solve design and functionality challenges with minimal supervision. Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON. Hands-on experience designing and building scalable applications using SQL and NoSQL databases. Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle. Proficiency in automation and continuous delivery methods. 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. Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security. Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). Preferred qualifications, capabilities, and skills: Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management. Strong problem-solving, analytical, and communication skills. Ability to drive broader impact by sharing and contributing best practices. Experience in the banking domain. AWS certification. Experience in building enterprise solution focused on Data Analytics will be beneficial Experience in LLM based implementations will be beneficial