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Lead Software Engineer- Java Full Stack, AWS, Kafka

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Onsite

Lead Software Engineer- Java Full Stack, AWS, Kafka

JPMC

Lead Software Engineer- Java Full Stack, AWS, Kafka

Skills

JavaSpring BootKafkaAIAWS

2 months ago

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Important information


Contract type:

Permanent

Location:

Plano, TX, USA

Work mode:

Onsite

Published on:

18 August 2026

What they need


As a Lead Software Engineer at JPMorganChase within the CONSUMER & COMMUNITY BANKING team, you are an integral part of an agile team that works to 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 conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

 Job responsibilities

  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • 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.
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Serves as a function-wide subject matter expert in one or more areas of focus
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software  Development Life Cycle
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Strong OOP/design patterns understanding and clean code practices
  • Strong coding skills in Java and Springboot with solid fundamentals
  • 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.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proven, hands-on experience across system design, application development, testing, and production support
  • Experience with low-latency/high-throughput systems

Preferred qualifications, capabilities, and skills

  • Exposure to agentic AI

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