Lead Software Engineer - Backend/Java/Cloud at JPMorgan Chase, Plano, TX
Lead Software Engineer - Backend/Java/Cloud at JPMorgan Chase in Plano, TX. Est. up to $200k. Apply with swipeandhired.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within Consumer & Community Banking - Fraud Assessment Tech team, you are an integral part of an agile team that enhances, builds, and delivers trusted market-leading technology products in a secure, stable, and scalable way. You will be a core technical contributor, driving critical technology solutions across multiple technical areas and business functions in support of the firm’s objectives. You will collaborate closely with product partners and engineering peers to design resilient systems, improve developer experience, and raise the bar on quality and operational excellence.
Job responsibilities:
- Design and deliver scalable, resilient Java-based services and microservices using modern engineering practices
- Build and maintain API-driven solutions (REST) and distributed, event-driven architectures
- Develop and optimize data pipelines and streaming solutions using Apache Kafka
- Model, query, and tune relational and NoSQL data stores to support performance, integrity, and scale
- Implement and improve continuous integration and continuous delivery pipelines to enable safe, frequent releases
- Apply infrastructure-as-code practices to create repeatable, reliable environments and deployments
- Monitor production systems, troubleshoot issues, and drive improvements in availability, latency, and reliability
- Conduct code reviews and contribute to engineering standards for secure coding, testing, and documentation
- Partner with stakeholders to translate business needs into technical designs and production-ready solutions
- 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:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- 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.
- 8+ years of Java experience, including core APIs, web services, concurrency, and design patterns
- 8+ years of Spring Boot experience building high-performance, maintainable services
- 5+ years of experience with SQL and NoSQL databases, including data modeling and performance tuning
- 5+ years of Apache Kafka experience designing and implementing event-driven solutions
- 2+ years of cloud experience, including deploying and operating services using Amazon Web Services
- Proven ability to design, develop, deploy, and support medium to large applications in an agile (Scrum) environment
- Proficiency building secure, scalable RESTful APIs and microservices
- Experience implementing CI/CD using tools such as Jenkins, GitLab CI, Spinnaker, or AWS CodePipeline
- Hands-on experience with automated testing frameworks such as JUnit 5 and Cucumber
Preferred qualifications, capabilities, and skills:
- Experience with modern DevOps practices and infrastructure-as-code tooling such as Terraform
- Experience with performance testing, debugging, and profiling using tools such as JMeter or BlazeMeter
- Experience with observability and monitoring tools such as Splunk, CloudWatch, Prometheus, Dynatrace, or Grafana
- Experience with containerization and orchestration using Docker and Kubernetes
- Demonstrated mentoring and technical coaching experience that supports team growth and continuous improvement