Lead Software Engineer - Python/react, Ansible, Rhel

JPMorgan Chase JPMorgan Chase · Banking · Columbus, OH +1 · Corporate Sector

Lead Software Engineer role focused on designing, developing, and supporting automation-enabled software solutions using Python, React, and Ansible on RHEL. The role emphasizes driving improvements in reliability, usability, and delivery practices, and includes leading the adoption of AI-assisted engineering practices for code quality, delivery speed, and operational outcomes.

What you'd actually do

  1. Own end-to-end delivery of software capabilities using Python (services, APIs, integrations, automation tooling) and React (UI workflows, API-driven front-ends).
  2. Drive design decisions and establish engineering standards (code quality, testing strategy, CI/CD patterns, release discipline).
  3. Build and scale automation and tooling capabilities to improve operational efficiency and user experience.
  4. Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  5. Develop and maintain automation solutions using Ansible Automation Platform (playbooks/roles, inventories, credential patterns, operational runbooks).

Skills

Required

  • Python
  • React
  • Ansible Automation Platform
  • RedHat Enterprise Linux (RHEL)
  • Software engineering concepts
  • API integrations
  • Web application development
  • Debugging
  • Testing
  • Customer support
  • Incident ownership
  • Root Cause Analysis (RCA)
  • Stakeholder communication
  • Basic networking concepts (DNS, TLS/certificates, connectivity)

Nice to have

  • TypeScript
  • Modern React patterns
  • UI testing (Jest/RTL/Cypress)
  • Python frameworks (FastAPI/Flask)
  • Async patterns
  • Packaging
  • Linting
  • CI
  • Ansible best practices
  • Observability (structured logging, metrics, tracing)
  • On-call rotations
  • Containers (Podman/Docker)
  • Orchestration (Kubernetes/OpenShift)
  • Proxies/firewall concepts
  • Load balancers

What the JD emphasized

  • Deep Python engineering experience
  • Strong experience building web applications with React
  • Hands-on experience with Ansible Automation Platform
  • Practical experience supporting systems on RedHat Linux / RHEL
  • Demonstrated experience leading effective use of approved AI-assisted software development tools
  • Strong understanding of responsible AI use in engineering workflows