Software Engineer III - Java Full Stack Developer + Python + AWS

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Java Full Stack Developer + Python + AWS at JPMorgan Chase within the Commercial & Investment Bank, you'll serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. 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.

Job responsibilities
- Design, develop, and maintain scalable and robust applications using Java, Spring Boot and React.
- Collaborate with cross-functional teams to define, design, and ship new features.
- Implement cloud-native solutions on AWS, ensuring high availability, scalability, security and Engage in prompt engineering for LLMs and write Python scripts.
- Utilize AI tech tools such as GitHub Copilot and MCP servers to enhance productivity and code quality.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Participate in code reviews, providing constructive feedback to peers.
- Troubleshoot and resolve complex technical issues across the application stack.
- Stay up-to-date with emerging technologies and industry trends, and apply them to improve existing systems and processes.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies 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 3+ years applied experience
- Proven experience in software development using Core Java, REST, Spring Boot, Spring modules, Hibernate, Junit and Mockito.
- Experience in UI technologies like jQuery, HTML, React and Strong skills around design principles and design patterns with the ability to troubleshoot and debug an application for any application issues.
- Strong understanding of cloud platforms - AWS and experience deploying applications in a cloud environment.
- Experience with CI/CD pipelines, containerization (Docker, Kubernetes), version control systems (Git) and messaging and integration frameworks like Kafka.
- Experience in writing SQL queries, database management concepts, JDBC, and persistence API frameworks like Spring JPA.
- Experience in AI/ML with focus on Generative AI, AI Agents Framework like Lang chain and Lang graph, Python, LLMs, RAG, Prompt engineering.
- Excellent problem-solving skills and the ability to work independently and collaboratively in a team environment.
- Strong communication skills, both written and verbal, with the ability to articulate complex technical concepts to non-technical stakeholders and Ability to multi-task and also work independently in order to meet the committed deadlines and Knowledge in Spec Driven development architecture.
- 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.
Preferred qualifications, capabilities, and skills
- Platform engineering experience
- Good knowledge in Syndicated deals
- Experience in the financial services industry or a similar regulated environment.