Full Stack Java Software Engineer III - React / AI / Kubernetes
On-siteChicago, Illinois, United States
Job Summary
Design and deliver trusted market-leading technology products by executing software solutions, development, and technical troubleshooting across multiple technical areas. Create secure, high-quality production code in Java and React, while designing event-driven architectures and real-time data streaming solutions using Kafka for high-throughput financial processing. Build, deploy, and manage containerized applications with Kubernetes, optimize Oracle data models and queries, and leverage enterprise-authorized AI coding tools to improve code quality and delivery speed. Produce architecture artifacts, analyze large datasets for system improvements, and apply agile methodologies including CI/CD and application resiliency within the Global Banking Technology team at JPMorganChase.
Required Qualifications
- Formal training or certification on software engineering concepts
- 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Proficiency in Java for backend development with demonstrated experience building and maintaining scalable, production-grade applications
- Hands-on experience with React for building dynamic, responsive, and user-facing front-end applications
- Demonstrated experience with Oracle database development including data modeling, query optimization, and stored procedure development
- Hands-on experience with Kafka for building event-driven, real-time data streaming solutions in a production environment
- Experience deploying and managing containerized workloads using Kubernetes in a production or enterprise environment
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Desired Qualifications
- Experience applying structured critical thinking and advanced problem-solving methodologies to diagnose and resolve complex, ambiguous technical challenges in a large enterprise environment
- Familiarity with cloud-based platforms and services, particularly AWS (e.g., S3, Lambda, EC2, or equivalent), to complement containerized and on-premise architectures
- Exposure to infrastructure-as-code tools such as Terraform or Helm for managing Kubernetes deployments and cloud infrastructure
- Experience working within financial services or highly regulated enterprise environments with a strong understanding of data security and compliance requirements
- Knowledge of distributed systems design patterns, microservices architecture, and API development best practices
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