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)
