AI Testing Architect

Job Description Benefits:Competitive salaryHealth insuranceOpportunity for advancementJob Title: AI Testing Architect (GenAI / QA Automation)Work Type: Full-Time/Contract Location: Dallas, Texas Onsite Interview Mode: Virtual + In-Person (depends)Work Auth : Must be authorized to work in the U.S. Domain: Enterprise AI / Agentic AI / AWS BedrockCompensation: Competitive, commensurate with experienceWe are hiring a senior AI Testing Architect to design and implement AI-driven solutions across software testing and quality engineering. This role focuses on applying Generative AI to improve test coverage, reduce cycle time, and modernize QA practices.You will work hands-on with engineering and QA teams while also guiding tooling decisions and adoption approaches. This is a high-impact individual contributor role with ownership of architecture, implementation, and practical AI adoption across testing workflows.Key ResponsibilitiesDesign and implement AI-driven solutions for test automation, test data generation, and defect detectionBuild and deploy LLM-based workflows (e.g., test case generation, RAG-based validation, anomaly detection)Evaluate, select, and integrate AI tools and frameworks for QA and SDLC use casesDevelop reusable architecture patterns for AI-enabled testing across teamsIntegrate AI solutions into CI/CD pipelines and existing engineering workflowsCollaborate with Engineering, QA, and DevOps teams to drive practical AI adoptionOptimize performance, cost, and reliability of AI-based solutions in productionProvide technical guidance and hands-on support to engineers adopting AI toolsContribute to lightweight AI governance practices, including data handling, security, and responsible usageRequired Qualifications8+ years of experience in software engineering, QA automation, or test architecture3+ years of hands-on experience with AI/ML or Generative AI in production environmentsStrong experience with test automation frameworks (Selenium, Playwright, Cypress, PyTest, TestNG)Strong programming skills in PythonExperience building or integrating LLM-based solutions (prompting, RAG, embeddings, vector search)Experience integrating solutions into CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps)Experience with at least one cloud platform (AWS, Azure, or GCP)Strong understanding of software testing principles, QA processes, and SDLCPreferred QualificationsExperience with LangChain or LlamaIndexExperience with vector databases (Pinecone, FAISS, Weaviate)Exposure to MLOps practices and model lifecycle managementExperience with AI governance, security, or compliance frameworksPrior experience as an AI Architect, Solution Architect, or Principal EngineerExperience working in enterprise-scale environmentsTechnical StackLanguages: Python (primary), Java or JavaScript (optional)Testing: Selenium, Playwright, Cypress, PyTest, TestNGAI/GenAI: OpenAI APIs, LangChain or LlamaIndex, embeddings, RAGData: Vector databases (Pinecone, FAISS, Weaviate)Cloud: AWS, Azure, or GCPCI/CD: Jenkins, GitHub Actions, Azure DevOpsSuccess MetricsReduce regression testing cycle time through AI-driven automationImprove test coverage and defect detection using AI-generated test assetsDeliver reusable AI architecture patterns adopted across teamsDrive measurable adoption of AI tools within engineering and QA workflows