GenAI Automation QE Lead

Location: Charlotte, NC Onsite
Duration: 6+ Months
Experience: 13+ Years

Job Overview

We are seeking an experienced GenAI Automation QE Lead with 13+ years of experience in Quality Engineering, Test Architecture, Test Automation, and enterprise-scale testing programs. The ideal candidate will have strong expertise in automation frameworks and modern Generative AI technologies, with hands-on experience applying GenAI and Agentic AI capabilities across the Software Testing Life Cycle (STLC).

The candidate will be responsible for driving the adoption of AI-driven quality engineering solutions, designing scalable automation frameworks, developing GenAI-assisted testing solutions, and providing technical leadership across enterprise testing initiatives.

Key Responsibilities

GenAI Solutions in STLC

• Design, build, and test GenAI solutions to generate test automation code for UI and API testing using automation tools and GenAI-assisted coding.
• Develop and implement Generative AI solutions for test data mining, generation, and optimization.
• Leverage GenAI for test design, test case generation, execution, defect analysis, and root-cause analysis.
• Identify opportunities to integrate AI-driven solutions throughout the Software Testing Life Cycle.
• Evaluate and implement Agentic AI capabilities to improve test automation and quality engineering processes.

Architecture & Design

• Participate in the architecture, design, and implementation of scalable automation frameworks and GenAI-driven quality engineering solutions.
• Design and implement solutions involving fine-tuning pipelines, prompt engineering frameworks, RAG architectures, and AI agents.
• Develop reusable and scalable AI-driven testing frameworks for enterprise applications.
• Participate in cross-functional GenAI initiatives, Proof of Concepts (PoCs), and innovation programs across the software development lifecycle.
• Evaluate emerging AI technologies and recommend solutions aligned with enterprise quality engineering objectives.

Strategy & Roadmap

• Define and execute the Automation and GenAI adoption roadmap in alignment with business and technology objectives.
• Identify opportunities to modernize existing automation practices using Generative AI and Agentic AI.
• Evaluate build-vs-buy decisions and provide recommendations on AI platforms, tools, and vendor solutions.
• Establish best practices for AI-driven test automation and quality engineering.
• Advocate for responsible AI practices, security, compliance, and model governance.

Collaboration & Technical Leadership

• Collaborate with Data Scientists, ML Engineers, Software Engineers, Product Managers, Architects, and other key stakeholders.
• Provide technical leadership for enterprise-scale automation and GenAI initiatives.
• Mentor and guide QE and automation teams on GenAI best practices and emerging AI technologies.
• Promote best practices related to model optimization, deployment, monitoring, security, and AI safety.
• Lead technical discussions, design reviews, PoCs, and implementation initiatives.
• Communicate complex AI and automation concepts effectively to both technical and business stakeholders.

Required Technical Skills

• 13+ years of experience in Quality Engineering, Test Architecture, Test Automation, and enterprise-scale testing.
• Strong proficiency in Python and Java.
• Strong hands-on experience with Selenium and Playwright.
• Extensive experience in API Automation and Testing.
• Experience designing and building scalable automation frameworks.
• Hands-on experience with Generative AI and AI-assisted test automation.
• Knowledge of Agentic AI, Prompt Engineering, RAG, and LLM-based solutions.
• Experience applying GenAI to test design, test generation, test execution, test data generation/mining, and defect analysis.
• Experience with LLM ecosystems and AI platforms, including one or more of:
  • Azure OpenAI
  • AWS Bedrock
  • LangChain
  • LangGraph
  • GitHub Copilot
  • Anthropic Claude / Claude Code
• Experience with AI-driven automation frameworks and integration of LLMs into testing workflows.
• Strong understanding of software testing methodologies, CI/CD, DevOps, and modern engineering practices.

Preferred Skills

• Experience developing or implementing AI agents for Quality Engineering.
• Experience with LLM fine-tuning and model evaluation.
• Knowledge of AI model governance, responsible AI, security, and compliance.
• Experience integrating GenAI solutions with enterprise automation frameworks.
• Strong understanding of cloud platforms and cloud-native application testing.
• Experience leading GenAI/Automation PoCs and transitioning successful PoCs into production solutions.
• Excellent communication, problem-solving, stakeholder management, and technical leadership skills.