Sr. Architect - SRARCH

TekWissen • Charlotte, NC

12d • Onsite

About The Position

We are seeking a GenAI Automation QE Lead with 13-16 years of experience in Quality Engineering, Test Architecture, and Automation. The ideal candidate will have proven leadership in enterprise-scale testing programs and a strong understanding of the Software Testing Life Cycle (STLC). This role involves building and testing solutions for UI/API automation using AI-assisted coding and leveraging Generative AI for test data mining. You will also participate in the design and implementation of Automation Frameworks, fine-tuning pipelines, and prompt engineering frameworks. A key aspect of this role is defining the Automation/GenAI adoption roadmap, evaluating build-vs-buy decisions, and advocating for responsible AI practices. Collaboration with data scientists, ML engineers, product managers, and stakeholders is essential, as is mentoring teams in GenAI best practices.

Requirements

• 13-16 years of experience in Quality Engineering, Test Architecture, and Automation
• Proven leadership in enterprise-scale testing programs
• Strong proficiency in Python, Java, Selenium, Playwright, API Automation, and building scalable AI-driven testing frameworks
• Learning/Hands-on expertise in Generative AI, Agentic AI, Prompt Engineering, RAG, and AI-assisted test automation for test design, execution, and defect analysis
• Learning/Experience with LLM ecosystems and AI platforms such as Azure OpenAI, AWS Bedrock, LangChain, LangGraph, GitHub Copilot, and Anthropic Claude Code

Responsibilities

• Build/Test Solution to create test automation code for UI/API through Automation tool/GenAI assisted coding
• Build/Test solution for test data mining using Generative AI
• Participate in design and implementation of Automation Framework, solutions, fine-tuning pipelines, and prompt engineering frameworks
• Participate in cross-functional GenAI initiatives and PoC’s across entire software lifecycle
• Define Automation/GenAI adoption roadmap in alignment with client goals
• Evaluate build-vs-buy decisions and advise on vendor/platform selections
• Advocate for responsible AI practices and model governance frameworks
• Collaborate with data scientists, ML engineers, product managers, and key stakeholders
• Mentor teams in GenAI best practices, including model optimization, deployment, and safety measures

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed