Full Stack Software Engineer III - Java
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Key skills for this role
Key Skills for This Role
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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
About JPMorgan Chase
Global financial services and investment banking firm.
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