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JP Morgan Chase Logo

Lead Software Engineer - Java

JP Morgan Chase

Salary not specified
Sep 9, 2025
New York, NY, USA
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Enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner within the Commercial & Investment Bank's Payments Technology team.

Requirements

  • Hands-on experience in system design, application development, testing, and ensuring operational stability.
  • Advanced proficiency in Java, J2EE, and RESTful/GraphQL web services for enterprise-scale application development.
  • Experience with event streaming technologies such as Apache Kafka and Apache Flink.
  • Experience with Docker and Kubernetes.
  • Proficiency with NoSQL databases (e.g., Cassandra, DynamoDB) and relational databases.
  • Experience in automation and continuous delivery methods.
  • Proficient in all aspects of the Software Development Life Cycle (SDLC) within Agile methodology.

Responsibilities

  • Design, develop, and troubleshoot creative software solutions, thinking beyond conventional approaches to solve complex technical problems.
  • Develop secure, high-quality production code; review and debug code written by others.
  • Modernize legacy systems to cloud-native architectures.
  • Identify opportunities to automate or remediate recurring issues, improving operational stability of applications and systems.
  • Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials.
  • Champion communities of practice across Software Engineering to promote awareness and adoption of new technologies.

Other

  • Formal training or certification in software engineering concepts, with 5+ years of applied experience.
  • Foster a team culture of diversity, opportunity, inclusion, and respect.
  • Advanced understanding of agile practices, including CI/CD, application resiliency, and security.
  • Demonstrated ability to build and maintain software applications in technical disciplines such as cloud, artificial intelligence, or machine learning.
  • Practical experience with cloud-native architectures and deployments.