AI QE Architect
Charlotte, VT - USA
Job Summary
Job role: AI QE Architect
Location : Charlotte North Carolina
Job Summary
Position Overview
We are seeking an AI QE Architect to serve as a dedicated AI Change Agent for our 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 customers existing environment.
Core Responsibilities
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 DevOps 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.
Technical Skills & Qualifications
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. LangChain CrewAI AutoGen 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.
DevOps & Cloud: Hands-on experience with GitHub 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.