Role: AI Tools & Testing Architect
Location: Dallas, TX
Duration: Long-Term
AI Tools & Testing Architect
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.
Responsibilities
The AI Tools & Testing Architect will play a pivotal role in defining and leading the adoption of AI technologies within our software development lifecycle (SDLC). This includes architecting AI solutions, ensuring they are integrated into our testing and quality assurance processes, and collaborating with various teams to embed AI across the organization.
- AI Architecture & Implementation:
- Architect, design, and implement AI-driven solutions across software testing and QA, quality engineering, and 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, and 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, and 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.
- Mentor & Technical Leadership:
- Act as a technical mentor and advisor.
- Guide teams and stakeholders (technical and non-technical) on AI adoption strategies.
Requirements
<>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, and Retrieval-Augmented Generation (RAG).
- Proven experience designing scalable AI architectures.
- Deep understanding of software testing methodologies, QA processes, and test automation frameworks.
- Experience integrating AI into CI/CD pipelines, DevOps, and MLOps workflows.
- Familiarity with cloud-based AI platforms and APIs, including AWS, Azure, and Google Cloud Platform.
- Strong ability to translate business problems into AI-driven technical solutions.
- Excellent communication and stakeholder management skills.
<>Preferred Skills & Experience
- Experience with DevOps and MLOps workflows.
- Knowledge of enterprise security, data privacy, and ethical AI standards.
- Experience with AI governance and responsible AI practices.
