Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Sr Lead Software Engineer - Platform Engineering at JPMorgan Chase within the Commercial & Investment Bank - Payments Technology Space, you are 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Design, build, and maintain a proprietary Java framework built on Spring Boot — starters, auto-configuration, dependency management, and integration with standard libraries for messaging, data, and observability
- Own and evolve the framework versioning and release strategy — supporting multiple active major versions simultaneously while managing consumer migrations deliberately
- Build and maintain the test automation strategy for the framework: unit, integration, and contract tests that give the team confidence that changes are safe before they reach the ~1,000+ application teams that consume each release
- Conduct rigorous, high-quality PR reviews — explaining the why behind feedback, raising the technical standard of the local team through the review process
- Own the team's approach to containerized delivery — including framework integration with managed container images, container runtime behavior, and how the framework layer interacts with the platform's image strategy
- Contribute to shared platform services — the running services that the framework wires applications into at runtime; understanding the full build-to-runtime picture is essential
- 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
- Actively participate in global platform design discussions with counterparts in other locations, representing Austin's perspective and contributing to cross-site architectural decisions
- Diagnose and resolve complex, cross-cutting issues where root cause is in the framework layer rather than in any individual consumer application
- Apply system design principles to framework and platform problems — making and clearly communicating critical design decisions with long-lived consequences
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Significant Java engineering experience with demonstrable depth in framework or platform library development — candidates should be able to speak to versioning, compatibility, and testing challenges specific to shared library work
- Strong understanding of Spring Boot internals — auto-configuration, condition evaluation, bean lifecycle, and how framework code interacts with application context
- Experience building and maintaining test automation for library/framework code, including integration test harnesses that exercise real downstream behavior
- Understanding of semantic versioning, backward compatibility contracts, and multi-version support strategies — ability to reason about what constitutes a breaking change and manage consumers through one
- Solid experience with containerized applications and container runtime systems — including managed container image strategies, image layering, runtime concerns (JVM/GC arguments, sidecar patterns), and how framework choices affect container behavior
- 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
- Hands-on experience with core cloud CI/CD tooling — including infrastructure-as-code (Terraform) and deployment pipeline tooling (Spinnaker); understanding of how platform software is built, versioned, and deployed in a cloud-native environment
- Strong system design skills with the ability to demonstrate critical thinking on architectural trade-offs — particularly decisions that affect a large consumer base over multiple years
- Proven track record as a technical lead — mentoring engineers, conducting substantive code reviews, and raising the quality of a team's output, not just individual output
Preferred qualifications, capabilities, and skills
- Experience with Kafka, Cassandra, or OpenTelemetry instrumentation at the framework/starter level
- Prior experience building or maintaining an internal Java framework built on Spring Boot, or equivalent proprietary platform library in a large organization
- Experience in a large-scale engineering organization — where decisions affect many teams, migrations require coordination at scale, and platform stability is a hard constraint
- Background in financial services — understanding of the regulatory, audit, and controls environment that shapes how platform software is built and operated in a bank
- Experience working across geographically distributed teams in a senior or lead capacity