Lead Software Engineer - Sdet

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Corporate Sector

Lead Software Development Engineer in Test (SDET) responsible for designing, building, and supporting automated testing frameworks for backend applications. The role emphasizes driving team adoption of enterprise-authorized AI-assisted engineering practices, ensuring quality, speed, and operational outcomes, while adhering to responsible AI use principles and validation standards.

What you'd actually do

  1. Design and support automated testing frameworks for backend applications
  2. Develop and maintain test scripts using Python3 and pytest
  3. Implement and validate REST API functionality and principles
  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. 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.

Skills

Required

  • Prior experience as an SDET or Software Developer
  • Proficiency in Python3
  • Experience designing and supporting automated testing frameworks for backend applications
  • Demonstrated experience leading effective use of approved AI-assisted software development tools
  • Strong understanding of responsible AI use in engineering workflows
  • Understanding of REST API design
  • Hands-on experience with Docker containers
  • Experience with at least one cloud provider: AWS, Azure, or GCP
  • Experience creating CI/CD pipelines

Nice to have

  • pytest
  • monitoring tools (Prometheus, Grafana, ELK, Datadog, Splunk, etc.)
  • backend frameworks like Spring, Micronaut, or Dropwizard
  • Kubernetes
  • non-functional testing
  • Infrastructure-as-Code concepts and tools like Terraform
  • Experience designing and supporting automated testing frameworks for frontend applications

What the JD emphasized

  • enterprise-authorized AI-assisted engineering practices
  • Demonstrated experience leading effective use of approved AI-assisted software development tools
  • Strong understanding of responsible AI use in engineering workflows