Benefits:
- Onsite
- Competitive salary
- Opportunity for advancement
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