Job Description

Join us to advance your software engineering career while building impactful technology solutions. Grow your skills and make a difference with a collaborative team.

As a Software Engineer II at JPMorgan Chase within the Chief Technology Office team, you will design, develop, and deliver innovative software solutions. You will collaborate with an agile team to enhance technology products in a secure and scalable way. You will gain hands-on experience across the software development lifecycle. You will contribute to a supportive team culture focused on growth and technical excellence.

Job Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate 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.
• 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

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and 5+ years of applied experience or as per firm’s guidelines.
  • Strong Python development skills with a track record of delivering large-scale projects
  • Experience with relational databases such as Sybase, MS SQL Server, or Oracle
  • Good understanding of the Software Development Life Cycle (SDLC)
  • Experience developing, debugging, and maintaining code in large-scale enterprise applications and strong understanding of data structures, algorithms, and their practical use
  • Hands-on experience with system design, application development, testing, and operational stability and experience in tech and/or financial industries
  • 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.
  • Solid understanding of Agile practices, including CI/CD, application resiliency, and security and ability to work effectively in a dynamic, fast-paced environment with multiple concurrent projects
  • Strong collaboration skills to work with stakeholders across teams to clarify business/product questions.

Preferred qualifications, capabilities, and skills

• Familiarity with shell scripting in Linux/UNIX environments
  • Strong understanding of mathematical concepts and statistical analysis
  • Working knowledge of Python numerical libraries such as NumPy and Pandas
  • Exposure to cloud technologies, including AWS solutions and storage technologies
  • Exposure to AI tools (e.g., Claude, Copilot)