Director, AI Quality Engineering & Assurance, Wipro

Director
Karnataka, India, Bengaluru
September 21, 2026
Full Time

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Job Description

Wipro is currently recruiting for a Director of AI Quality Engineering & Assurance position based out of Bengaluru. This role entails developing enterprise level quality strategies for artificial intelligence-enabled products, platforms, and intelligent automation offerings. Some of the key responsibilities of this job include testing in AI and ML, RAG validation, responsible AI governance, testing automation, and quality transformation.

Qualification: Bachelor’s Degree/Master’s Degree preferred

Experience: 15+ years

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Responsibilities

  • Implement enterprise-wide quality engineering of AI, testing approaches, governance models, and quality standards for AI.
  • Oversee testing and validation of AI/ML, generative AI, RAG, agentic AI, chatbots, and AI assistants.
  • Champion Responsible AI practices with regard to security, privacy, regulatory compliance, risk management, and audit readiness.
  • Advocate for AI-driven test automation, synthetic data creation, predictive quality analytics, and performance monitoring.
  • Serve as global head of quality, reporting quality metrics and risks to executive sponsors.

Requirements

  • 15+ years in Quality Engineering, Test Management, or Quality Leadership.
  • At least 5 years leading large-scale QA organizations through digital transformation programs.
  • Real experience across AI/ML, Generative AI, LLM evaluation, RAG architecture validation, and Agentic AI testing.
  • Working knowledge of cloud platforms, test automation, API and microservices testing, data engineering, and MLOps.
  • A track record managing global teams, complex quality portfolios, and security/privacy/Responsible AI controls.

Preferred Qualifications

  • Expertise in Azure OpenAI, Microsoft Copilot, OpenAI, Gemini, Claude, and enterprise AI platforms.
  • Experience with developing an AI governance framework and implementation of Responsible AI principles.
  • Familiarity with observability and evaluation tools like LangSmith, MLflow, Prompt Flow, TruLens, or DeepEval.
  • Background running AI Quality initiatives in banking, healthcare, insurance, retail, or tech.
  • Experience in adjacent roles like AI cloud consulting, enterprise transformation, quality automation, or technology strategy.

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