GenAI Automation QE Lead

ReqRoute,Inc; Charlotte (NC); On-site; USD 140,000 - 230,000; Full time

Job summary

ReqRoute,Inc seeks an Enterprise GenAI Architect to lead AI-driven testing transformations in Charlotte, NC. You will shape architecture, vendor choices, and governance for scalable GenAI platforms within the SDLC and QA ecosystems.

You'll mentor distributed engineering and QA teams, drive adoption roadmaps, and collaborate with data scientists, developers, and stakeholders to deliver measurable improvements in quality, velocity, and cost efficiency.

Qualifications

• Hands-on with Generative AI and agentic testing approaches.
• Experience leading large-scale enterprise QE transformations.
• Strong Python/Java and AI-enabled test automation design.

Responsibilities

• Lead GenAI adoption across AI-driven testing lifecycle for QA workflows.
• Design intelligent agents for test design, script creation, and auto-migration.
• Define adoption roadmap, governance, security, and model lifecycle.
• Collaborate with data scientists, architects, and product owners.
• Mentor teams on best practices and AI-first engineering.
• Evaluate emerging AI technologies and prototypes.
• Drive improvements in productivity, quality, and release velocity.

Skills

GenAI & Agentic AI

Prompt engineering

Automation strategy

Leadership & mentoring

Tools

Python

Java

Selenium

Playwright

API automation

LangChain

LangGraph

Semantic Kernel

Azure OpenAI

AWS Bedrock

GitHub Copilot

Anthropic Claude

Job description

Job Title: Enterprise GenAI Architect
Location: Onsite in Charlotte, NC

Job Description/ Responsibilities:

AI-Driven Test Automation Transformation:

• Lead the adoption of GenAI-powered automation across the Software Testing Lifecycle (STLC), driving productivity, quality, and speed-to-market.
• Accelerate UI, API, and end-to-end test automation through AI coding assistants and agentic development platforms such as GitHub Copilot, Claude Code, and similar technologies.
• Design and implement intelligent agents for test case generation, test design reviews, automation script creation, defect analysis, self-healing automation, and legacy script migrations.
• Establish AI-assisted testing practices to improve test coverage, reduce manual effort, and enhance overall delivery efficiency.

Architecture & Solution Design:

• Contribute to the architecture, design, and implementation of enterprise-grade GenAI solutions and agentic frameworks.
• Develop and optimize prompt engineering strategies, retrieval workflows, and model orchestration patterns to improve solution accuracy and reliability.
• Collaborate in the design and deployment of scalable AI platforms that integrate seamlessly into SDLC and QA ecosystems.
• Participate in cross-functional GenAI initiatives, innovation programs, and Proofs of Concept (PoCs) spanning the entire software development lifecycle.

Strategy & Roadmap:

• Define and execute the GenAI adoption roadmap for Quality Engineering, aligned with client objectives, business priorities, and technology strategies.
• Assess build-versus-buy options and provide recommendations on AI platforms, tools, models, and vendor partnerships.
• Drive AI governance, responsible AI practices, security considerations, compliance standards, and model lifecycle management frameworks.
• Establish success metrics and value realization strategies to measure AI adoption and business impact.

Collaboration & Leadership:

• Partner with data scientists, ML engineers, architects, product owners, developers, and business stakeholders to deliver AI-powered solutions.
• Mentor engineering and QA teams on GenAI best practices, agentic workflows, prompt engineering, model optimization, deployment strategies, and AI safety principles.
• Foster a culture of innovation, continuous learning, and AI-first engineering across teams.
• Act as a thought leader and trusted advisor for GenAI adoption within the organization and client engagements.

Innovation & Experimentation:

• Continuously evaluate emerging AI technologies and identify opportunities to transform QA operations and software delivery processes.
• Develop prototypes and accelerators using modern AI frameworks such as LangChain, LangGraph, Semantic Kernel, MCP, AI Skills, and multi-agent architectures.
• Explore advanced use cases including autonomous testing agents, conversational quality engineering assistants, intelligent release validation, and predictive quality analytics.
• Drive experimentation and innovation initiatives that improve engineering effectiveness, reduce costs, and enhance software quality outcomes.
• 16 20 years of experience in Quality Engineering (QE), Test Architecture, and Test Automation, with a proven track record of leading large-scale enterprise testing transformations and quality assurance programs.

What are the top skills required for this role?

• Hands-on expertise in Generative AI and Agentic AI, including Prompt Engineering, Retrieval-Augmented Generation (RAG), AI-powered test automation, and leveraging AI for intelligent test design, execution optimization, root cause analysis, and defect prediction.
• Strong technical proficiency in Python, Java, Selenium, Playwright, API Automation, and the design and implementation of scalable, reusable, and AI-enabled test automation frameworks.
• Deep understanding of LLM ecosystems and AI platforms, including Azure OpenAI, AWS Bedrock, LangChain, LangGraph, GitHub Copilot, Anthropic Claude, and related AI orchestration frameworks.
• Proven ability to define and execute Quality Engineering strategies, automation roadmaps, governance models, and best practices, while leading globally distributed teams and delivering measurable improvements in productivity, quality, release velocity, and cost efficiency.