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JPMorganChase

Software Engineer III-Java, Kafka, AWS

Posted An Hour Ago
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Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Mid level
Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Mid level
Design, develop, and maintain scalable, secure payment systems. Produce architecture and high-quality production code, troubleshoot complex issues, build integrations, leverage cloud and messaging (Kafka/ActiveMQ), use AI-assisted development tools, and contribute to continuous improvement and team practices within an agile environment.
The summary above was generated by AI

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorgan Chase within the Commercial & Investment Bank Payments Technology team, you will be an experienced member of an agile team, tasked with designing and delivering reliable, market-leading technology products that are secure, stable, and scalable.
 

Job responsibilities


  • Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  • Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  • Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
  • Contributes to software engineering communities of practice and events that explore new and emerging technologies
  • Adds to team culture of diversity, opportunity, inclusion, and respect
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  • 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 3+ years applied experience
    Hands-on practical experience in system design, application development, testing, and operational stability
  • Hands-on  expertise in Java development, messaging systems (ActiveMQ, Kafka), RESTful APIs, software design principles, relational database management systems (RDBMS) and cloud technologies
  • Design, develop (Rewrite and Re-Arch) and maintain scalable, high-performance applications, ensuring robust integration and deployment in cloud environments
  • Proficient in coding in one or more languages
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Overall knowledge of the Software Development Life Cycle
  • Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.


Preferred qualifications, capabilities, and skills


  • Familiarity with modern front-end technologies
  • Exposure to cloud technologies

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