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 Developer + Python + AI + Elastic search 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 • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems • Develops secure high-quality production code (primarily Java / Spring Boot), and reviews and debugs code written by others • Leads the design and delivery of scalable microservices/APIs within the Spring ecosystem (e.g., Spring MVC/WebFlux, Spring Data, Spring Security), with strong testing practices • Proactively improves engineering productivity using AI4Tech practices, including hands-on use of Copilot/Claude Code for refactoring, test generation, documentation, and code modernization—while ensuring correctness and secure coding standards • Builds and operationalizes AI agents that integrate with engineering workflows (e.g., PR review assistants, runbook/support agents, remediation assistants), including tool/function calling, structured outputs, and safety/guardrails • Uses Python as needed for AI/agent prototyping, automation, evaluation harnesses, or glue code/integrations • 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 • Hands-on practical experience delivering system design, application development, testing, and operational stability • Advanced Java development experience with strong fundamentals (OO design, concurrency, performance, debugging) • Strong hands-on experience with Spring Boot and related frameworks (REST APIs, security, persistence), Elastic search, plus unit/integration testing. • AI4Tech hands-on experience using Copilot/Claude Code (or similar approved tools) to accelerate delivery while maintaining code quality, security, and test coverage • Experience building AI agents / LLM-enabled workflows, including prompt discipline, grounding/verification strategies, and safe handling of sensitive data • Some experience or working knowledge of Python (scripting, automation, or AI/agent prototyping) • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security • Practical experience on Kubernetes • 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 • Experience designing and operating production-grade agentic systems (observability, evals, prompt/versioning, fallbacks, rate limits, and guardrails) • Experience with modern microservice patterns (resiliency, distributed tracing, event-driven design)