Java Lead Software Engineer - Kafka

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As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Payment Platform 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

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Lead and inspire a team of entry-level to mid-level software engineers, fostering a culture of collaboration, innovation, and excellence
• Oversee technical design, architecture, and implementation to ensure high-quality, scalable solutions
• Produce architecture and design artifacts for complex applications, ensuring that design constraints are met during software code development
• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to support continuous improvement of software applications and systems
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineering concepts and 8+ years applied experience
• 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
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Ability to tackle design and functionality problems independently with little to no oversight
• Proficiency in Java, REST, and microservices, with experience building event-driven microservices and Kafka streaming
• Experience with Spring Framework, Spring Boot, and public or private cloud infrastructure
• Proven record of providing end-user support with excellent problem-solving abilities

Preferred qualifications, capabilities, and skills

• Exposure to AI - using python, AI, Copilot in VScode/Intellij
• knowledge of Containerization and Container Runtime/Orchestration platforms (Docker/Kubernetes/ECS etc)
• knowledge about messaging – Kafka
• knowledge about Relational/NoSQL databases