AI Tools & Testing ArchitectDallas, TX OnsiteLong-Term DuraitonWe are seeking a highly experienced AI Tools & Testing Architect with deep, hands-on expertise in designing, implementing, and scaling AI-driven solutions across software engineering—particularly in testing, quality engineering, and SDLC optimization. This role combines technical architecture, strategic advisory, and hands-on enablement, helping engineering and QA teams effectively adopt AI to improve productivity, quality, and time-to-market. You will act as a technical architect and AI evangelist, guiding organizations in selecting the right AI tools, defining adoption frameworks, and embedding AI responsibly into engineering workflows. Key Responsibilities AI Architecture & Implementation

• Architect, design, and implement AI-driven solutions across:   Software testing and QA   Quality engineering   Broader software engineering workflows
• Design scalable, secure, and reusable AI reference architectures.AI for Testing & Quality Engineering
• Define and lead AI adoption frameworks for testing use cases, including:   Automated test case generation and optimization   Test data generation, synthesis, and masking   Defect prediction, anomaly detection, and root-cause analysis   Intelligent test execution, prioritization, and coverage optimizationTooling & Platform Strategy
• Evaluate, select, and recommend AI tools, platforms, and vendors, including:   LLMs, agents, copilots   AI-powered test automation tools   Internal and external AI platforms
• Optimize AI tool integration for performance, cost, and reliability. Engineering Enablement & Collaboration
• Collaborate with Engineering, QA, DevOps, Security, and Leadership teams to embed AI across the SDLC.
• Enable teams with:   Best practices   Design patterns   Reference implementations
• Conduct workshops, demos, and enablement sessions. Governance & Responsible AI
• Establish AI governance, security, and responsible AI guidelines
• Ensure compliance with enterprise security, data privacy, and ethical AI standards. Mentorship & Technical Leadership
• Act as a technical mentor and advisor
• Guide teams and stakeholders (technical and non-technical) on AI adoption strategies. Required Skills & Experience
• Strong hands-on experience with AI/ML and Generative AI, including:
• Large Language Models (LLMs)                 Prompt engineering                   AI agents                     Embeddings and vector search                     Retrieval-Augmented Generation (RAG)
• Proven experience designing scalable AI architectures
• Deep understanding of:
• Software testing methodologies             QA processes             Test automation frameworks
• Experience integrating AI into:
• CI/CD pipelines             DevOps and MLOps workflows
• Familiarity with cloud-based AI platforms and APIs:
• AWS             Azure             GCP
• Strong ability to translate business problems into AI-driven technical solutions
• Excellent communication and stakeholder management skills Nice to Have
• Experience with AI governance, security, and compliance
• Prior role as:
• AI Architect           Solution Architect             Principal Engineer
• Experience implementing AI in enterprise-scale environments
• Certifications in:
• Cloud platforms         AI/ML           Architecture frameworks Success Criteria
• Demonstrated impact in: 
• Improving testing efficiency         Enhancing software quality         Reducing time-to-market using AI 
• Delivery of clear, reusable AI reference architectures and best practices 
• High adoption, engagement, and satisfaction across engineering and QA teams