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Lead Software Engineer - Java, AI, Spring Boot and Kafka

Skills

agileaiapiautomationawsazureci cdcloudcloud nativedata pipelinesevent driven architectureflinkgcpgrafanagraphqlhelmhibernateinfrastructure as codejavajpajunitkafkakubernetesmicroservices

Description

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 the Commercial & Investment Bank’s Digital and Platform Services organization, you are an integral part of the Equipment & Asset Finance Technology team. You will help 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 delivering critical technology solutions across multiple technical areas and business functions in support of the firm’s objectives.

Equipment & Asset Finance Technology supports equipment leasing, lease origination, asset valuation and tracking, portfolio servicing, and asset lifecycle management across multiple lines of business. In this role, you will serve as a technical lead for the next-generation Equipment & Asset Finance platform, a multiyear strategic investment delivering modern lease origination, asset valuation, and lifecycle management capabilities at enterprise scale.
Job responsibilities

  • Executes creative software solutions, design, development, testing, and technical troubleshooting, with the ability to think beyond conventional approaches to solve complex technical problems
  • Develops secure and high-quality production code, reviews and debugs code written by others, and ensures solutions meet architectural standards and automated quality requirements
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards 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
  • Leads a global feature team by setting technical direction, supporting pair programming, mentoring engineers, contributing to architectural decisions, and partnering with Product Owners, Operations, and Technology teams
  • Identifies opportunities to improve application stability, observability, code quality, and deployment reliability while supporting applications across development, staging, and production environments

Required qualifications, capabilities, and skills

  • Formal training or certification in software engineering concepts and 8+ years of applied experience, including hands-on delivery of system design, application development, testing, and operational stability
  • Advanced Java development experience, including Java 21+, object-oriented analysis and design, concurrency, collections, streams, records, sealed classes, pattern matching, and virtual threads
  • Advanced experience with Spring Boot 3.x / Spring Framework 6.x, including Spring Security, Spring Data, microservices, domain-driven design, RESTful APIs, OpenAPI 3.x, and event-driven development with Kafka
  • Hands-on full-stack and data experience using React 18+, TypeScript, relational databases such as Oracle SQL / PostgreSQL, and persistence frameworks including Hibernate / JPA
  • Demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to validate AI outputs for correctness, performance, security, and responsible handling of sensitive data, combined with advanced knowledge of Agile delivery, continuous integration and delivery, application resiliency, and security

Preferred qualifications, capabilities, and skills

  • Experience with React hooks, context, state-management tools, component design systems, and Next.js 14+
  • Cloud-native development experience with AWS, Azure, or GCP, including managed compute, storage, messaging, and secrets-management services
  • Experience with Kubernetes, Helm, and infrastructure-as-code tools such as Terraform or Pulumi
  • Experience with automated testing and observability tools, including JUnit 5, Mockito, Testcontainers, Pact, OpenTelemetry, Prometheus, and Grafana
  • Experience with Redis, GraphQL, and data-pipeline technologies such as Apache Spark or Flink
  • Experience in production support, incident management, financial services, equipment leasing, lease accounting, asset valuation, commercial lending technology, or asset lifecycle workflows

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