Senior Lead Software Engineer - Java/Python; AWS, Kubernetes
Posted Updated
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 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:
As a Senior 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
