Backend Software Engineer III Java Kafka

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As a Backend Software Engineer III Java Kafka at JPMorgan Chase within the Consumer and Community Banking, 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
• Develops secure 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.
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; f
• Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
• Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
• Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
• 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
• Proficient in all aspects of the Software Development Life Cycle including advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Led design and delivery of Kafka-based event streaming platforms/services in high-throughput (high TPS) environments; deep experience with event-driven architecture patterns and distributed systems reliability.
• Experience improving operability (SLOs/SLAs, on-call readiness, monitoring, incident response, postmortems) for streaming systems.

Preferred qualifications, capabilities, and skills

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