Software testing • dallas tx
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The average salary range is between $ 80,006 and $ 152,000 year , with the average salary hovering around $ 107,500 year .
Benefits:
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
