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AI Evaluation Lead

Exclusive opportunity

Onsite

AI Evaluation Lead

QualityKiosk Technologies

AI Evaluation Lead

Skills

Testing & QAMachine LearningAINLP / Natural Language ProcessingComplianceRegulatory ComplianceDigital TransformationRisk Management

23 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

1 October 2026

What they need


JOB DESCRIPTION – AI Evaluation Lead / Principal Consultant

Role Summary We are looking for an AI Evaluation Lead / Principal Consultant to own the strategy, methodology, commercial growth, and leadership direction of the AI Evaluation practice. This is a senior leadership role focused on scaling AI quality capabilities, building flagship accounts, shaping enterprise AI evaluation programs, and establishing thought leadership in AI assurance.

Experience Required

12+ years of total experience. Candidates should have 5+ years of experience in AI, ML, NLP, LLMs, AI quality, enterprise AI delivery, AI evaluation, or AI assurance, with 3+ years in team leadership, practice leadership, or senior client advisory roles.

📩 Share your profile at: [email protected]

Key Responsibilities

  • Define and own the AI Evaluation practice strategy, operating model, methodology direction, and quality standards.

  • Build and scale enterprise AI evaluation offerings across voice AI, chatbots, LLM applications, agentic AI, and multimodal AI.

  • Own flagship client relationships and engage senior executives on AI quality, AI risk, and AI assurance.

  • Shape high-value AI evaluation programs for enterprise clients. • Define commercial models, effort estimation approaches, delivery structures, and margin discipline for evaluation engagements.

  • Lead solutioning, proposals, presales discussions, and strategic account expansion.

  • Build reusable frameworks for hallucination testing, robustness testing, red teaming, safety evaluation, compliance evaluation, and regression testing.

  • Guide L3/L2 leaders and develop the leadership bench for the evaluation practice.

  • Own hiring strategy, senior talent development, and succession planning.

  • Identify new market opportunities, domains, modalities, partnerships, and adjacent offerings.

  • Represent the practice externally through industry forums, client workshops, publications, advisory discussions, and thought leadership.

  • Drive methodology adoption internally and externally.

  • Ensure delivery quality, client satisfaction, revenue growth, and long-term practice scalability.

Required Knowledge and Skills

Expert-level understanding of AI evaluation, LLM evaluation, AI quality, conversational AI, and enterprise AI assurance.

  • Strong knowledge of hallucination evaluation, robustness testing, safety testing, red teaming, responsible AI, and compliance-oriented evaluation.

  • Strong understanding of enterprise AI delivery models, AI lifecycle risks, governance, and quality assurance.

  • Strong executive stakeholder management and consultative selling ability.

  • Proven experience building teams, practices, offerings, or large-scale delivery capabilities.

  • Ability to define commercial strategy, pricing approach, delivery economics, and account growth plans.

Strong methodology design and thought leadership capability.

  • Ability to mentor senior practitioners and create successors. • Strong communication, executive presentation, negotiation, and strategic planning skills. • Ability to work across delivery, product, sales, client leadership, and partner ecosystems.

Preferred Skills • Experience leading an AI testing, AI quality, AI assurance, AI governance, or AI evaluation practice. • Experience with AI evaluation and testing platforms. • Strong network in AI, digital transformation, quality engineering, or enterprise technology. • Experience publishing thought leadership, white papers, case studies, or speaking at industry events. • Experience in regulated industries such as BFSI, healthcare, insurance, automotive, or telecom. • Exposure to Responsible AI frameworks, model risk management, AI governance, and regulatory compliance.

Educational Qualification B.E. / B.Tech / M.Tech / M.S. in Artificial Intelligence, Computer Science, Computer Engineering, Information Technology, or related Computer discipline.

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