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Software Engineer II

JPMorgan Chase
Bengaluru, IND
Full-time
Junior · 2+ years experience
Onsite
Discovered 2 days ago

Full Job Posting

Job responsibilities

  • Executes standard software solution, design, development, and technical troubleshooting
  • Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
  • Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
  • 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
  • Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
  • Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
  • Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 2+ years applied experience.
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Develop, debug, and maintain code in a large corporate environment using one or more modern programming languages and database querying languages.
  • Use enterprise-authorized, AI-assisted software development tools (for example, for coding, testing, troubleshooting, or documentation) while critically evaluating and validating AI-generated outputs.
  • 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 across the whole Software Development Life Cycle
  • Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

  • Exposure to AI technologies
  • Knowledge on Cloud

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