Software Engineer III - Java Developer + Python + Agentic AI

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)