About this role
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the CIB / Payments Technology, you serve as a seasoned member to design, build, and support reliable, scalable payment applications. The ideal candidate has strong Java experience, including reactive programming, and can develop cloud-native, event-driven services using AWS and Kafka. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will also help identify practical ways to apply AI capabilities to payment products and engineering workflows.
Job Responsibilities
- Design, develop, test, and maintain payment applications and services using Java and reactive programming frameworks such as Spring WebFlux or Project Reactor.
- Build event-driven services and streaming workflows with Apache Kafka.
- Develop, deploy, and operate cloud-native applications on AWS.
- Contribute to secure, resilient payment processing, including transaction lifecycle, authorization, settlement, reconciliation, and exception handling.
- Create and maintain RESTful APIs and service integrations.
- Apply engineering practices such as automated testing, code reviews, CI/CD, observability, and performance tuning.
- Partner with product, architecture, operations, risk, and other engineering teams to deliver payment capabilities.
- Explore and implement appropriate AI-enabled solutions, such as intelligent exception handling, anomaly detection, developer productivity tools, or payment operations support.
- Support production services, investigate incidents, and contribute to root-cause analysis and service improvements.
Required Qualifications, Skills and Capabilities
- Professional software development experience with Java.
- Hands-on experience with reactive programming and asynchronous, non-blocking application design.
- Experience building distributed, event-driven applications with Apache Kafka.
- Experience developing or operating applications on AWS.
- Strong understanding of APIs, microservices, distributed systems, and database technologies.
- Experience with automated testing, source control, and CI/CD practices.
- Ability to communicate clearly and collaborate across technical and business teams.
Preferred Qualifications, Skills and Capabilities
- Experience with payment systems, financial transaction processing, or other high-volume, high-availability platforms.
- Familiarity with AWS services such as EKS, ECS, Lambda, API Gateway, SQS, SNS, DynamoDB, RDS, CloudWatch, and IAM.
- Experience with Kafka schema management, partitioning, consumer groups, replay, and delivery semantics.
- Knowledge of application security, encryption, secrets management, and regulatory considerations relevant to payments.
- Experience with containers and orchestration technologies such as Docker and Kubernetes.
- Familiarity with AI/ML services or platforms, including integrating model APIs, retrieval-augmented generation, or AI-assisted workflow automation.
- Understanding of responsible AI practices, including data privacy, explainability, evaluation, and human oversight.