Java Backend Lead Software Engineer Kafka AWS

JPMorganChase•Wilmington, NC

About The Position

As a Java Backend Lead Software Engineer in JPMorgan Chase’s Consumer and Community Banking organization, you will contribute to an agile team building and enhancing secure, stable, scalable technology products. You will deliver technical solutions across multiple areas in support of business objectives, lead technical direction, and improve the quality, speed, and operational outcomes of software delivery. The role includes developing and reviewing production code, guiding responsible adoption of approved AI-assisted engineering tools, addressing recurring operational issues, evaluating technical designs, and sharing leading-edge practices across Software Engineering.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Hands-on experience delivering system design, application development, testing, and operational stability.
Proficiency in backend technologies such as Java, Spring Boot, or Node.js, and experience building microservices-based applications.
Ability to independently solve design and functionality challenges with minimal supervision.
Experience with cloud platforms such as AWS, Azure, or GCP; distributed systems; and web technologies, including RESTful APIs, web services, WebSockets, and JSON.
Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, and setting expectations for validating outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
Experience leading the design and delivery of Kafka-based event-streaming platforms or services in high-throughput environments, with deep experience in event-driven architecture patterns and distributed-systems reliability.
Experience improving operability of streaming systems, including SLOs/SLAs, on-call readiness, monitoring, incident response, and postmortems.

Nice To Haves

Strong presentation, negotiation, mentoring, and stakeholder-management skills.
Strong problem-solving, analytical, and communication skills.
Ability to contribute to broader impact by sharing and contributing best practices.
AWS certification.
Production experience building and operating high-volume data-processing pipelines using Apache Spark (Spark SQL, Structured Streaming) and/or Apache Flink (DataStream/Table API).

Responsibilities

Execute software design, development, and technical troubleshooting, using creative approaches to address technical problems.
Develop secure, high-quality production code and review and debug code written by others.
Lead team adoption of enterprise-authorized AI-assisted engineering practices, establish validation standards, and promote reuse of effective patterns.
Use software development lifecycle tools, including authorized AI-assisted development and automation capabilities, to improve automation outcomes.
Identify opportunities to eliminate or automate recurring issues and improve application and system stability.
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and fit with existing systems and information architecture.
Lead Software Engineering communities of practice to increase awareness and use of new technologies.
Drive technical direction, architecture decisions, design documentation, stakeholder alignment, and delivery through ambiguity.
Improve operability of streaming systems, including SLOs/SLAs, on-call readiness, monitoring, incident response, and postmortems.
Coach engineers on safe and compliant adoption of AI-assisted tools in delivery practices.