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JPMorganChase

Software Engineer II

Posted 2 Days Ago
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Hybrid
Mumbai, Maharashtra
Junior
Hybrid
Mumbai, Maharashtra
Junior
Contribute to design, development, testing, and operational stability of secure, scalable software components. Write and validate high-quality code, use enterprise AI-assisted development tools, troubleshoot incidents, analyze large datasets, and improve automation and SRE outcomes within Agile teams.
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You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you. 


As a Software Engineer II at JPMorgan Chase within the Corporate & Investment Bank, Merchant Services, you are part of an agile team that designs, enhances, and delivers secure, stable, and scalable software components for the firm’s state-of-the-art technology products. In this emerging engineering role, you contribute to the end-to-end execution of software solutions—including design, development, and technical troubleshooting—across multiple components of applications and systems, while building the skills and experience needed to advance and grow within your role.

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
  • Uses enterprise-authorized AI capabilities within the work environment to speed up incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
  • 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
  • Applies enterprise-authorized AI capabilities within the work environment to identify recurring toil and reliability risks from operational signals, prioritizing reuse-first improvements and measurable SLO outcomes.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 2+ years applied experience ( NAMR/APAC – India/ LATAM/ Hong Kong)
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate 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.
  • Working knowledge of using enterprise-authorized AI capabilities within the work environment to support SRE workflows (e.g., troubleshooting support and runbook drafting) with strong validation habits and awareness of data sensitivity. 
  • Ability to assess AI-assisted operational recommendations for correctness and risk, and apply appropriate controls to maintain resiliency, security, and auditability.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools (e.g., Copilot, Claude Code) within the work environment for coding, testing, troubleshooting, or documentation, with demonstrated ability to critically evaluate and validate AI-generated outputs through rigorous code review and testing practices.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

Preferred qualifications, capabilities, and skills

  • Full stack Java developer experience in enterprise application development
  • Strong experience in SDLC delivery in Agile methodologies
  • At least two years experience in Java 17+
  • Experience developing microservices, packaged into AWS Elastic Kubernetes Service and/or Elastic Container Service, and deployed to EC2 instances
  • Experience writing Terraform scripts and deploying in AWS production environment
  • Experience in at least one relational database management system (preferably Oracle or PostgreSQL)

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