AI Tools & Testing Architect
Dallas, TX Onsite
Long-Term Duraiton

We 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 optimization
 
Tooling & 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