AI QE Architect

Job Title: AI QE Architect

Location: Charlotte, North Carolina (onsite)

Employment Type: contract

We are seeking an AI QE Architect to serve as a dedicated AI Change Agent for our customer. In this role, you will lead the transition from traditional Quality Engineering to an AI-augmented ecosystem. You will be responsible for defining the strategy, building high-impact AI use cases, and modernizing the QE landscape using Generative AI and Agentic frameworks.

A critical component of this role is deep familiarity with Claude Code, as it is a core tool within the customer s existing environment.

• Strategy & Assessment:
  Evaluate the current QE landscape (tools, frameworks, processes, and team maturity). Define and drive a comprehensive Agentic AI-led QE transformation roadmap.
• AI Implementation:
  Design and implement hands‑on AI‑driven QE solutions, including:
  • Autonomous Test Generation:
    Creating test cases and scripts using LLMs.
  • Self‑Healing Automation:
    Building frameworks that automatically adapt to UI/code changes.
  • Intelligent Analytics:
    Developing defect prediction models and automated triaging systems.
  • Synthetic Data:
    Implementing AI‑driven test data generation.
  • Ecosystem Modernization:
    Integrate AI capabilities into existing CI/CD pipelines and Dev Ops workflows to accelerate delivery.
  • Tooling & R&D:
    Evaluate next‑gen QE platforms, build Proof of Concepts (POCs), and develop reusable accelerators for scalable adoption across the enterprise.
• Leadership (Player‑Coach):
  Act as a hands‑on technical leader who can both architect high‑level strategy and contribute directly to code and implementation.
• Stakeholder Management:
  Collaborate with business, product, and engineering leadership to communicate progress, outcomes, and the value of AI initiatives.

• Foundational
  
  Experience:
  
  10 14 years of experience in Quality Engineering or Software Development in Test (SDET), with a track record of leading enterprise‑scale transformations.
• AI & GenAI Expertise:
  Proven experience with Agentic AI and GenAI frameworks (e.g., Lang Chain, CrewAI, Auto Gen, or Cursor).
• Specific knowledge of Claude Code and its application in development/testing workflows.
• Deep understanding of LLMs and multi‑agent systems applied to QE.
• Core QE Proficiency:
  Expertise in modern automation tools like Playwright, Selenium, or Cypress.
• Strong grasp of API testing, microservices, and cloud‑native architectures.
• Dev Ops & Cloud:
  Hands‑on experience with Git Hub Actions and CI/CD integration.
• Familiarity with cloud platforms (AWS, Azure, or GCP) in the context of AI and testing.
• Execution:
  Ability to build POCs from scratch and scale them into production‑ready frameworks.
• Communication:
  Exceptional ability to explain complex AI concepts to non‑technical stakeholders and senior leadership.