Enterprise QA AI Architect: Strategy, Governance & Scale

VISION INFOTECH INC.; Georgia; Hybrid; USD 150,000 - 210,000; Full time

Job summary

VISION INFOTECH INC. seeks a Senior AI Architect to lead AI strategy, governance, architecture, and adoption across a global QA organization.

The role partners with QA leadership, engineering, and enterprise architecture to establish scalable AI standards and reusable patterns for accelerated adoption with reduced risk. This leadership role requires blending enterprise architecture with execution governance in software testing, QA automation, generative AI, and AI-enabled engineering

Qualifications

• Extensive experience in AI architecture and enterprise architecture.
• Strong knowledge of Generative AI, LLMs, AI agents, and orchestration.
• Experience designing AI solutions within large, complex enterprise environments.
• Proven ability to govern AI initiatives, risk, compliance, and validation.
• Experience translating architecture concepts into executive roadmaps.
• Solid background in QA automation and AI-enabled testing practices.

Responsibilities

• Define AI strategy, governance, operating model, and KPI framework for QA.
• Architect enterprise AI solutions for software testing and QA transformation.
• Lead vendor evaluations, scorecards, and technology selection.
• Partner with security, data, and Responsible AI teams to ensure standards.
• Drive adoption of reusable AI capabilities and governance templates.
• Oversee POC governance and transition to production-ready capabilities.

Skills

AI architecture

Enterprise architecture

QA automation

Generative AI

LLMs

AI governance

Vendor management

Communication skills

Tools

Azure DevOps

GitHub Copilot

Microsoft Copilot

Power BI

Tricentis Tosca

UFT

Job description

VISION INFOTECH INC. seeks a Senior AI Architect to lead AI strategy, governance, architecture, and adoption across a global QA organization.

The role partners with QA leadership, engineering, and enterprise architecture to establish scalable AI standards and reusable patterns for accelerated adoption with reduced risk. This leadership role requires blending enterprise architecture with execution governance in software testing, QA automation, generative AI, and AI-enabled engineering