The AI Evaluation Lead / Principal Consultant will own the strategy, methodology, commercial growth and leadership direction of the AI Evaluation practice.
This senior leadership role focuses on scaling AI quality capabilities, building strategic enterprise accounts, shaping AI evaluation programs and establishing thought leadership in AI assurance.
This role combines deep AI evaluation expertise with practice leadership, enterprise consulting, commercial strategy, executive stakeholder management and the ability to build scalable AI assurance capabilities.
- 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 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.
Hallucination Testing
Design systematic approaches to identify and measure unreliable AI outputs.
Robustness Testing
Evaluate AI behavior across variations, edge cases and challenging inputs.
Red Teaming
Establish adversarial testing and AI safety evaluation programs.
Safety Evaluation
Assess harmful, unsafe and undesirable model behavior.
Compliance Evaluation
Align AI evaluation programs with enterprise governance and compliance needs.
Regression Testing
Establish repeatable evaluation processes for continuously evolving AI systems.
The role requires ownership beyond technical delivery, including practice strategy, commercial planning, solutioning, pricing, effort estimation and delivery economics.
The AI Evaluation Lead will also build leadership capability through mentoring, hiring, succession planning and development of senior practitioners.
Strong executive communication, negotiation, strategic planning and consultative selling are important for working across delivery, product, sales, client leadership and partner ecosystems.
- 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.
- Executive stakeholder management and consultative selling capability.
- Proven experience building teams, practices, offerings or large-scale delivery capabilities.
- Ability to define commercial strategy, pricing approaches, delivery economics and account growth plans.
- Strong methodology design and thought leadership capability.
- Ability to mentor senior practitioners and develop future leaders.
Who Fits This Role?
A senior AI consulting and quality leader with 12+ years of overall experience, including 5+ years across AI/ML, NLP, LLMs, AI quality, AI evaluation or AI assurance, and 3+ years in leadership or senior client advisory roles. The candidate should combine deep AI evaluation knowledge with practice building, commercial strategy, executive engagement, thought leadership and team development.
Total Experience
12+ years of professional experience.
AI Experience
5+ years in AI, ML, NLP, LLMs, AI quality, evaluation or assurance.
Leadership
3+ years in team leadership, practice leadership or senior client advisory.
B.E., B.Tech, M.Tech or M.S. in Artificial Intelligence, Computer Science, Computer Engineering, Information Technology or a related Computer discipline.
Candidates may share their profile at [email protected]