Lead Software Engineer Java and AIML

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank- Global Banking youare an integral part of an agile team that works to enhance build and deliver trusted market-leading technology products in a secure stable and scalable way. As a core technical contributor you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms 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 modernizationwhile 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

• Adds to team culture of diversity opportunity inclusion and respect

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality delivery speed and operational outcomes (e.g. AI-assisted code review/refactoring test strategy acceleration incident/root-cause analysis support) while establishing consistent validation standards (secure coding peer review automated testing) and promoting reuse of effective patterns across the team.

• 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

• 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

• 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.

• Strong understanding of responsible AI use in engineering workflows including data sensitivity considerations secure handling of inputs/outputs and adherence to resiliency and security expectations; experience coaching engineers on safe compliant adoption within delivery practices

• 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)