Drive significant impact at NTT DATA, a global leader renowned for technical excellence and innovation. We foster a diverse and inclusive workplace where you can grow and thrive.

This role is for a senior, customer-facing AI Architect Lead Advisor responsible for guiding complex, strategic customer engagements. You will translate ambiguous priorities into measurable outcomes, define paths from opportunity to production value, and ensure the optimal integration of various capabilities to meet customer needs.

The ideal candidate possesses deep expertise in a specialist discipline alongside a broad understanding of enterprise AI, technology platforms, industry dynamics, commercial models, and company/partner strengths. You will leverage judgment across domains, technologies, client relationships, and outcome leadership to shape high-impact opportunities and guide critical customer decisions.

Partner with executive and technical stakeholders to define strategic goals, key workflows, and measurable outcomes. Lead discovery and solution-shaping engagements, converting ambiguous customer priorities into a clear portfolio of opportunities and delivery decisions. Establish and manage outcome frameworks, including business ownership, baselines, targets, assumptions, dependencies, and evidence required for progression. Direct rapid prototyping and proof-of-concept efforts, focusing technical work on critical assumptions for customer value, adoption, and feasibility. Provide senior technical and solution judgment across AI, data, integration, architecture, security, privacy, Responsible AI, operational readiness, infrastructure, cost, and scalability. Shape strategic opportunities into production-ready solutions, ensuring maturity in architecture direction, backlogs, dependencies, acceptance criteria, estimates, governance, and mobilization. Build trusted relationships with executive stakeholders, acting as a senior advisor to simplify complexity, challenge constructively, and guide material customer decisions. Orchestrate specialist practitioners and teams across various functions to align around a single customer outcome. Lead the resolution of complex business, technical, operational, and organizational challenges using sound judgment and structured problem-solving. Identify and prioritize high-value opportunities by assessing domain context, customer strategy, technology capability, feasibility, adoption requirements, and business impact.

Possess deep domain and business awareness, understanding customer strategy, economics, operating constraints, and industry context. Demonstrate strong technical credibility across enterprise solution architecture, AI engineering, data, integration, cloud platforms, security, and production technology delivery. Exhibit broad applied understanding of artificial intelligence, generative AI, agentic systems, RAG, automation, and the implications of emerging AI technologies for enterprise transformation. Maintain a strong understanding of production AI considerations including evaluation, security, privacy, Responsible AI, observability, AgentOps, FinOps, resilience, and operational readiness. Display exceptional client emotional intelligence, executive communication, consulting, facilitation, stakeholder management, and relationship-building skills. Apply strong systems thinking, analytical judgment, problem-solving, experimentation, and evidence-based decision-making capabilities. Possess deep working expertise in at least one relevant specialist area such as AI engineering, architecture, industry, transformation, product, data, or AI infrastructure, with sufficient breadth to lead multidisciplinary engagements. Have broad knowledge of relevant company and partner platforms, products, accelerators, implementation methods, commercial offers, and reusable assets. Be able to rapidly understand unfamiliar domain context, including processes, terminology, regulation, data flows, organizational dynamics, user roles, constraints, and business metrics. Exercise strong commercial judgment, connecting solution choices to business value, risk, cost, time to value, adoption, and the appropriate delivery model. Demonstrate advanced outcome leadership, establishing measurable outcomes, challenging assumptions, prioritizing evidence, and driving key decisions. Maintain a strong reuse, product-feedback, and portfolio mindset, distinguishing customer-specific needs from scalable patterns and improvements. Communicate complex concepts and trade-offs clearly to diverse stakeholders using the appropriate level of detail. Operate independently in high-ambiguity situations, maintain momentum, challenge constructively, and make sound decisions with incomplete information. Influence senior technical and non-technical stakeholders across organizational boundaries without formal authority. Exhibit strong leadership, collaboration, mentoring, coaching, and knowledge-sharing skills.