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

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