Drimva

JPMorgan Chase

Lead Software Engineer - Full-Stack Java, React & AI

Plano, TX · Full-time · Posted Sep 14, 2026

Experience
5+ years of applied experience; 10+ years of hands-on enterprise software engineering experience.
Education
Formal training or certification on software engineering concepts.

About the job

Leads end-to-end design, development, and operation of enterprise managed-account software, while guiding engineers and responsible adoption of AI-assisted engineering practices.

What you'll do

  • Own application components across architecture, build, testing, deployment, observability, and production support; deliver secure, resilient, high-performance services and user experiences.
  • Lead technical discovery and implementation, partner with cross-functional stakeholders, and coach engineers on technical standards.
  • Adopt and guide AI-assisted development; validate generated changes and improve CI/CD, test automation, and developer experience.

What they ask for

  • 10+ years of hands-on enterprise software engineering using Java, J2EE, REST APIs, Spring Boot, Hibernate or another ORM, microservices, and relational databases such as Oracle or Sybase.
  • 5+ years of applied experience and formal training or certification on software engineering concepts.
  • Experience leading approved AI-assisted software development and coaching on safe, compliant use and validation of AI outputs.
  • Strong experience with scalable distributed systems, object-oriented design, DDD, microservices, cloud-native architecture, testing, SQL, CI/CD, and Agile delivery.

Nice to have

  • Front-end development with React, Angular, TypeScript, JavaScript, HTML, or Redux; event-driven processing with Kafka or comparable platforms.
  • AI coding assistants, observability tools, cloud platforms, or financial-services domain knowledge.

Tools

Java, J2EE, REST APIs, Spring Boot, Hibernate, Oracle, Sybase, React

AI focus

Use and lead responsible AI-assisted software development for coding, review, testing, troubleshooting, documentation, and modernization; provide repository and business context to AI agents, protect sensitive data, and validate outputs for correctness, performance, and security.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 4, 2026 (UTC)