Software Engineer III -python Fullstack - Ai/ml

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Corporate Sector

Software Engineer III role at JPMorgan Chase focused on Python Fullstack development within Corporate Technology. The role involves designing, developing, and troubleshooting technology solutions, creating secure production code, and producing architecture artifacts. It requires experience with Python, system design, containerization (Docker, Kubernetes), cloud-native development (AWS EKS), and agile methodologies. Familiarity with AI-assisted development tools and GenAI fundamentals for developer productivity is also mentioned.

What you'd actually do

  1. Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  2. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  3. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  4. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  5. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Skills

Required

  • Python Full-stack development
  • system design
  • application development
  • testing
  • operational stability
  • coding in modern programming languages
  • database querying languages
  • containerization technologies (Docker, Kubernetes)
  • container orchestration
  • cloud-native development
  • AWS EKS
  • CI/CD
  • Application Resiliency
  • Security
  • AI-assisted development tools
  • agentic coding workflows
  • GenAI fundamentals

Nice to have

  • modern front-end technologies
  • cloud technologies

What the JD emphasized

  • Python Full-stack development
  • system design, application development, testing, and operational stability
  • coding in one or more languages
  • developing, debugging, and maintaining code in a large corporate environment
  • containerization technologies (Docker, Kubernetes) and container orchestration in production environments
  • cloud-native development and AWS services, particularly AWS EKS
  • agile methodologies such as CI/CD, Application Resiliency, and Security
  • AI-assisted development tools and agentic coding workflows
  • GenAI fundamentals for developer productivity
  • software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)