AI Tools & Testing Architect

We are seeking a highly experienced AI Tools and Architecture Expert who has deep hands‑on expertise in using, implementing, and scaling AI solutions across software engineering, with a strong focus on testing and quality engineering use cases. This individual will act as a technical architect and strategic advisor, guiding teams on how to effectively adopt AI for productivity, quality, and innovation.

• Architect, design, and implement AI‑driven solutions across testing, QA, and broader engineering workflows
• Provide technical leadership and guidance on selecting, integrating, and optimizing AI tools (LLMs, agents, copilots, test‑automation AI, etc.)
• Define AI adoption frameworks for testing use cases such as:
  • Test case generation and optimization
  • Test data generation and masking
  • Defect prediction and root‑cause analysis
  • Intelligent test execution, coverage, and prioritization
• Enable teams with best practices, patterns, and reference architectures for AI usage
• Evaluate and recommend AI platforms, tools, and vendors based on business and technical fit
• Collaborate with engineering, QA, Dev Ops, security, and leadership teams to embed AI into the SDLC
• Establish governance, security, and responsible AI guidelines
• Mentor teams and conduct workshops, demos, and enablement sessions

• Strong hands‑on experience with AI/ML and generative AI tools (e.g., LLMs, prompt engineering, agents, embeddings, RAG)
• Proven architecture and design experience for scalable AI solutions
• Deep understanding of software testing, QA, and test‑automation frameworks
• Experience integrating AI with CI/CD pipelines and Dev Ops practices
• Familiarity with cloud‑based AI platforms (AWS, Azure, GCP) and APIs
• Ability to translate business problems into AI‑driven technical solutions
• Strong communication skills to guide both technical and non‑technical stakeholders

• Experience with AI governance, security, and compliance
• Prior experience as a Solution Architect, AI Architect, or Principal Engineer
• Experience implementing AI in enterprise‑scale environments
• Certifications in cloud, AI, or architecture disciplines

• Demonstrated impact in improving testing efficiency, quality, and time‑to‑market using AI
• Clear, reusable AI reference architectures and best practices
• High adoption and satisfaction across engineering and QA teams