Software Development Engineer

Adobe Adobe · Enterprise · San Jose, CA +2

Software Development Engineer role focused on enhancing a mobile automation engineering team's quality, speed, and scalability using AI. The role involves owning new functionality in the Mobile E2E framework, integrating it with the app codebase and AWS, debugging issues, defining test plans, and using AI tools for dashboards and test creation. Requires experience with mobile test frameworks, CI/CD, observability tools, AI code-generation/agentic tools, and mobile app development.

What you'd actually do

  1. Own the addition of new functionality to our Mobile E2E framework. Identify opportunities for improvement, apply AI techniques to inform design decisions, and implement capabilities that extend test coverage and keep pace with new features across iOS and Android
  2. Integrate and extend the bridge between our Mobile E2E framework, the mobile app codebase, and AWS orchestration infrastructure — contributing mobile app code, adding new automation workflows, and ensuring tests run reliably on real devices at scale
  3. Debug and investigate failures, memory, and performance issues across the Mobile E2E framework and native and web stacks. Feed diagnostic patterns back into AI tooling to build a feedback loop that drives triage efficiency
  4. Own test plan definition for assigned features — establishing coverage standards, providing examples, and promoting AI-guided test creation across teams and stakeholders to drive reliable, consistent test growth at scale
  5. Use AI tools to build dashboards that surface automation results into our observability and alerting framework. Track performance benchmarks, memory health, and quality trends across builds and devices

Skills

Required

  • 3+ years building and/or maintaining automated test frameworks for mobile software (iOS and/or Android)
  • Proficiency with CI/CD infrastructure and DevOps practices — AWS, BrowserStack, Jenkins, or CircleCI
  • Working experience using observability, debugging, and signal analysis tools — including Splunk, Charles Proxy, New Relic, and Grafana
  • Demonstrated experience using AI code-generation or agentic tools (e.g., Claude, Copilot, or similar LLMs) to accelerate automation work
  • Working experience in TypeScript and JavaScript
  • Working experience in developing native mobile apps

What the JD emphasized

  • AI techniques
  • AI tooling
  • AI-guided test creation
  • AI tools
  • AI code-generation or agentic tools
  • AI-generated outputs

Other signals

  • AI for quality automation
  • AI for test creation
  • AI for observability
  • AI-generated outputs validation