AI Quality Engineering Lead

Job Information

Core Skills

Key Responsibilities

• Lead enterprise AI Quality Engineering strategy and consulting engagements.
• Design AI-powered Quality Engineering ecosystems and reference architectures.
• Drive LLM and Agentic AI adoption strategies across enterprise projects.
• Architect scalable quality platforms integrating automation, analytics, and AI.
• Define AI governance, compliance, and regulatory quality standards.
• Lead rapid AI transformation initiatives delivering measurable business value.

Required Skills

• 15+ years of Quality Engineering experience.
• Enterprise Solution Architecture and Quality Engineering leadership.
• Strong expertise in AI Testing, LLMs, and Agentic AI.
• Experience with DevOps, SRE, and AI-powered engineering platforms.
• Knowledge of AI governance, compliance, and enterprise modernization.
• Ability to advise executive stakeholders on AI quality strategy.

Technology Expertise

• Large Language Models (LLMs)
• Agentic AI
• AI Quality Engineering Platforms
• Topaz Fabric QoS
• Devin AI
• Quality Intelligence Platforms
• Cloud AI Architecture
• DevOps & Site Reliability Engineering

Why This Role Matters

As enterprises adopt AI at scale, Quality Engineering is evolving from traditional testing to AI-driven strategy and intelligent quality ecosystems. This leadership role focuses on architecting enterprise AI quality platforms, integrating LLMs and Agentic AI, enabling governance, and delivering measurable business outcomes through modern AI-powered engineering practices.

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