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AI SDET

Job in Charlotte, Mecklenburg County, North Carolina, 28231, USA
Listing for: Saxon Global
Full Time position
Listed on 2026-05-25
Job specializations:
  • Software Development
    Software Engineer, DevOps, AI Engineer, Software Testing
Job Description & How to Apply Below
Overview

We are looking to add a Software Development Engineer in Test (SDET) to a high-performing AI product team. This is not a traditional QA role-we need a developer-minded engineer who can build automated testing frameworks from scratch and take ownership of quality engineering across a technical, AI-driven platform.

This is a greenfield testing environment, so the right candidate will be excited by the opportunity to define and build the testing strategy and infrastructure.

What We're Looking For
  • Developer-first mindset (not a manual QA tester)
  • Strong interest in automation, quality engineering, and testing systems
  • Comfortable working in a highly technical, AI-based product environment
  • Someone who can figure things out without pre-existing frameworks
Core Responsibilities
  • Design and build automated testing frameworks from scratch
  • Develop and maintain Python-based test automation
  • Partner closely with engineers to:
    • Understand how the application is supposed to work
    • Validate behavior and identify failure modes
  • Test AI-driven functionality, including:
    • Prompt-based workflows
    • Output validation and edge cases
  • Help define the overall testing strategy and best practices for the team
Required Skills
  • Strong Python experience (must-have)
  • Experience building automated test frameworks
  • Background as a developer or SDET (not just QA)
  • Ability to:
    • Write code confidently
    • Work in an unstructured / greenfield environment
  • Strong communication skills:
    • Must be able to understand application behavior and validate outcomes effectively
Nice to Have
  • Experience testing React-based front-end applications
  • Familiarity with AI/LLM ecosystems:
    • General understanding of LLMs, prompts, and AI workflows
    • Exposure to tools like Lang Chain / Lang Graph
  • Cloud experience (helpful but not required)
What Success Looks Like
  • Builds a scalable testing framework from the ground up
  • Becomes a key contributor in ensuring product quality and reliability
  • Helps the team better understand and test AI-specific behaviors and risks
  • Acts as a strong partner to engineering (not a downstream QA function)
Notes for Recruiting
  • Do not target traditional QA testers
  • Prioritize:
    • SDET profiles
    • Developers who moved into testing/automation
  • Look for candidates who are:
    • Comfortable building frameworks from scratch
    • Interested in AI-driven systems (even at a basic familiarity level)
  • Communication skills are critical (use J as the benchmark profile)
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