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# Lead Software Engineer - Java Backend

- **Company:** JPMorgan Chase & Co.
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Software Applications, Behavior-Driven Development, Cloud Engineering, Cloud Foundry, Software Quality, Code Review, Databases, Continuous Delivery, Continuous Integration, Software Debugging, Amazon DynamoDB, MapReduce, Spring Framework, Apache JMeter, Open Source Technology, Oracle (Applications), Queueing Systems, Software Tools, Software Deployment, Software Engineering, Software Systems, Spinnaker, Data Streaming, Strategies of Testing, Toolchain, Apache Cassandra, Grafana, Apache Spark, Containerization, Kubernetes, Cassandra, Production Code, Apache Kafka, Cucumber (Software), Splunk, Code Restructuring, Dynatrace, Jenkins, Programming Languages, Control M
- **Published:** August 28, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3362095061&tx=JP7771FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Formal training or certification in software engineering concepts with eight or more years of applied experience
 * Hands-on practical experience delivering system design, application development, testing, and operational stability
 * Advanced proficiency in one or more programming languages, including Java, Spring, AWS, Kubernetes, Kafka, MQ, Cassandra, Oracle, Spark, Control-M, Cloud Foundry, Kubernetes, PowerMock, JMeter, Splunk, Grafana, Dynatrace, Jenkins and etc.
 * Proficiency in automation and continuous delivery methods
 * Proficiency in all aspects of the Software Development Life Cycle
 * Advanced understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security
 * Demonstrated proficiency in cloud-native technologies, including experience with Amazon Web Services and Kubernetes
 * Experience with data streaming technologies such as Apache Kafka and message queuing systems
 * Demonstrated experience leading effective use of enterprise-authorized, AI-assisted software development tools - including coding, code review, test acceleration, and 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 and outputs, and adherence to resiliency and security expectations, with experience coaching engineers on safe and compliant adoption

Preferred qualifications, capabilities, and skills

 * Experience with distributed platforms such as Amazon Web Services Elastic MapReduce and Apache Spark
 * Experience developing open-source or internal libraries integrated into applications by other teams
 * Experience with behavior-driven development using Cucumber and continuous integration using Jenkins and Spinnaker
 * Experience with cloud-native software deployment on Amazon Web Services and Pivotal Cloud Foundry
 * Experience with database technologies such as Apache Cassandra, Oracle, or Amazon DynamoDB
 * Exceptional client relationship skills, including the ability to uncover true requirements underlying feature requests, recommend alternative technical approaches, and drive efforts to meet committed timelines

## Description

* Execute creative software solutions, including design, development, and technical troubleshooting, with the ability to think beyond conventional approaches to solve complex problems
 * Develop secure, high-quality production code, and review and debug code written by others
 * Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
 * Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented assessment of architectural designs, technical credentials, and applicability within existing systems
 * Lead communities of practice across software engineering to drive awareness and adoption of new and leading-edge technologies
 * Drive team adoption of enterprise-authorized, AI-assisted engineering practices - including code review, refactoring, test strategy acceleration, and incident analysis - to improve code quality, delivery speed, and operational outcomes
 * Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized through automation
 * Foster a team culture of diversity, opportunity, inclusion, and respect


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