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