Lead Software Engineer - Java/Python; AWS; Kubernetes

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 Corporate 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:

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Execute standard software solution design, development, and technical troubleshooting across Java, Python, and Node.js in distributed cloud environments
• Execute standard software solution design, development, and technical troubleshooting across Java, Python, and Node.js in distributed cloud environments
• Write secure, high-quality code using at least one programming language, applying best practices with limited guidance and contributing to peer code reviews
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Design, develop, and troubleshoot software with consideration of upstream and downstream systems and their technical implications across AWS and Kubernetes environments
• 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.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficiency in Java or Python as a primary development language, with experience developing, debugging, and maintaining code in a large corporate environment using one or more modern programming languages and database querying languages
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment - including for coding, testing, troubleshooting, or documentation - with demonstrated ability to critically evaluate and validate AI-generated outputs
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations
• Experience across the full Software Development Life Cycle, including design, development, testing, and deployment
• Exposure to agile methodologies and practices such as CI/CD, application resiliency, and security
• Working knowledge of containerization and orchestration technologies, including Kubernetes and Docker, within AWS cloud environments
• 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.
• Ability to tackle design and functionality problems independently with little to no oversight

Preferred qualifications, capabilities, and skills:

• Experience with Node.js for backend or full-stack development
• Exposure to infrastructure-as-code tools such as Terraform or AWS CloudFormation
• Familiarity with AI/ML frameworks and integrating intelligent capabilities into enterprise software applications
• Experience working with large-scale data pipelines or event-driven architectures
• Knowledge of financial services technology or regulated industry software development practices
• Practical cloud native experience