Join a team where your engineering decisions matter at scale. At JPMorganChase, we build production-grade software that powers critical Global Banking businesses — and we're looking for engineers who take ownership, raise the bar, and grow fast. You'll work in a culture of strong code reviews, fast feedback, and scalable architecture, with real opportunities to deepen your technical influence and shape the future of financial technology.
As a Software Engineer III at JPMorganChase within the Global Banking Technology team, you will own end-to-end delivery of secure, full stack features — turning requirements into solid designs, shipping clean Java code, and improving services built on microservices, Kafka/event-driven patterns, and CI/CD pipelines. You will troubleshoot complex production issues, drive performance and resiliency improvements, and automate recurring problems to strengthen operational stability. This role offers the opportunity to grow your technical influence, explore AI and GenAI patterns responsibly, and build a long-term engineering career within a firm that invests in its people.
Job responsibilities
- Lead delivery of complex features and services by shaping solution options, driving design decisions, and implementing scalable software that addresses ambiguous, multi-dimensional problems
- Own end-to-end engineering outcomes across design, build, test, release, and operate phases — ensuring security, resiliency, performance, and maintainability in production
- Set a high bar for code quality by authoring secure production code, leading code reviews, and debugging complex cross-service issues while continuously improving engineering standards and hygiene
- Drive operational excellence by identifying systemic failure patterns, implementing automation (self-healing, alerting, runbooks), and delivering sustainable fixes that measurably improve stability and resiliency
- Influence architecture and platform alignment by contributing to service boundaries, API and event contracts, data flows, and non-functional requirements across teams within enterprise constraints
- Partner on technical evaluations with internal teams, producing outcomes-oriented assessments of architecture, delivery readiness, security posture, and fit with existing platforms and information architecture
- Mentor and elevate team capability through pairing, design reviews, knowledge sharing, and contributing to communities of practice that accelerate adoption of modern engineering practices
- Promote an inclusive engineering culture by supporting a team environment grounded in diversity, opportunity, inclusion, and respect
- Produce architecture and design artifacts for complex applications while ensuring design constraints are met throughout software code development
- Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and proficient applied experience
- Demonstrated ownership of system design and delivery for production services, including testing strategy, release execution, and operational support
- Strong proficiency in Java and common frameworks such as Spring Boot, Hibernate, JPA, and Spring Kafka, including performance tuning and troubleshooting patterns
- Working knowledge of microservices and Kafka/event-driven architectures, including reliability patterns such as idempotency, retries, ordering, and dead-letter queues
- Experience implementing automation and continuous delivery, including build and test automation, CI/CD pipelines, and quality gates
- Proficiency across the full software development lifecycle — requirements, design, implementation, testing, release, and support — with clear documentation and traceability
- Strong understanding of Agile delivery, application resiliency, secure engineering practices, and operational readiness
- 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
Preferred qualifications, capabilities, and skills
- Experience with additional languages and frameworks such as .NET (C#) and Python
- Familiarity with modern front-end technologies such as React and/or Angular
- Experience with container platforms and platform-as-a-service environments, including Kubernetes and Cloud Foundry
- Familiarity with Generative AI tools and patterns — including prompt engineering, retrieval-augmented generation, and vector search/embeddings — and safe, secure adoption practices
- Familiarity with financial services technology environments and enterprise-grade controls and standards
- Practical experience with cloud-native development, including containerization, observability, resiliency patterns, and incident response participation
