AI Architect

• Establish and evolve the AI vision, roadmap, operating model, and governance framework for the QA organization.
• Develop an accountability model across AI planning, governance, architecture, vendor management, innovation, and value realization.
• Create centralized processes for AI use-case intake, prioritization, risk assessment, and approval.
• Establish governance checkpoints, stage gates, KPIs, and executive reporting for AI initiatives.
• Partner with enterprise architecture, security, data, and Responsible AI teams to ensure alignment with organizational standards.

Enterprise AI Architecture

• Design enterprise AI architecture supporting software testing and QA transformation.
• Define standards and recommended patterns for:
  • Large Language Models (LLMs)
  • Generative AI
  • AI agents and orchestration
  • Knowledge sources and retrieval
  • Data architecture
  • APIs and integrations
  • Prompt engineering
  • Model evaluation and validation
• Develop reusable reference architectures and technical patterns that can be leveraged across multiple teams and vendors.
• Establish architectural review processes for new AI initiatives and solutions.
• Ensure AI solutions are scalable, interoperable, secure, supportable, and aligned with enterprise architecture standards.