Benefits:

Competitive salary

Opportunity for advancement

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

Role Overview 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