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Salary
≈ $29k – $72k per year (Estimated)
Location
In office (Noida)
Seniority
Middle · 2+ years exp

Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 24, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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 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 standard software solutions, design, development, and technical troubleshooting
  • Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
  • 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 to improve the value realized by automation
  • Applies technical troubleshooting to break down 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
  • 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 2+ years applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Hands-on in Python, Java
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages. Demonstrable ability to code in one or more languages
  • Experience across the whole Software Development Life Cycle
  • Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security
  • Emerging 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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