Software Engineer II - Java/ Python / AWS / Kubernetes

Join one of the world's most innovative technology organizations and help shape the future of financial services through cutting-edge engineering. At JPMorganChase, your work isn't just code - it's infrastructure that moves markets, protects millions of customers, and drives real-world impact at global scale.

As a Software Engineer II at JPMorganChase within Corporate Technology in Houston, you will design, build, and maintain scalable cloud-native applications and AI-powered solutions that support critical business operations across the firm. You will collaborate with talented engineers and cross-functional teams to deliver high-quality, secure software using modern frameworks, cloud platforms, and intelligent automation. This role offers you the opportunity to grow your technical skills, contribute to meaningful products, and be part of a team that values innovation, inclusion, and continuous learning.

Job responsibilities

• 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
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity - including code generation, refactoring, unit test creation, and documentation - while validating outputs through peer review, automated testing, and secure coding standards
• Design, develop, and troubleshoot software with consideration of upstream and downstream systems and their technical implications across AWS and Kubernetes environments
• Apply knowledge of Software Development Life Cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation tools, to improve the value realized through automation
• Gather, analyze, and draw conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
• Build and integrate AI and machine learning frameworks into production-grade applications to solve complex business challenges
• Learn and apply system processes, methodologies, and engineering skills to support the development of secure, stable code and systems
• Participate in agile ceremonies, technical design discussions, and CI/CD pipeline development to support continuous delivery and operational stability

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience
• Hands-on practical experience in 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

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