Join NTT DATA, a global leader renowned for pushing technological boundaries and driving impactful innovations. We foster a diverse and inclusive workplace where you can achieve professional growth and belonging. As an AI Architect Senior Advisor, you will serve as a crucial customer-facing practitioner, bridging customer needs with cutting-edge technology solutions.

This senior role involves deep engagement within client environments, collaborating with business and technical stakeholders to address complex challenges. You'll leverage your expertise to make opportunities tangible and establish a clear path from initial concept to production value, combining specialized knowledge with a broad understanding of NTT DATA and partner platforms. Your role is pivotal in identifying high-impact opportunities and determining the most effective routes to achieve customer outcomes.

You will act as the consistent outcome advocate between clients and internal engineering, product, architecture, and operations teams. Your responsibilities include shaping validated opportunities into delivery-ready projects, staying involved through implementation and adoption, and utilizing customer feedback to drive continuous improvement. This position demands a blend of domain understanding, technical credibility, client emotional intelligence, and outcome leadership, enabling you to operate independently in ambiguous enterprise settings and lead complex engagements.

Partner with clients to understand business objectives and translate them into actionable opportunities. Lead discovery and solution-shaping activities, defining success measures and key assumptions. Develop rapid prototypes and experiments to validate critical assumptions related to value and feasibility. Assess solution feasibility across AI, data, architecture, security, privacy, and operational readiness. Shape validated opportunities into production-ready work packages, including architecture direction and backlog prioritization. Build trusted relationships with senior stakeholders, offering clear guidance and constructive challenge. Collaborate across various internal teams to orchestrate required capabilities for successful outcomes. Analyze and resolve complex technical and operational challenges using structured problem-solving. Identify high-value use cases by synthesizing domain context, stakeholder insights, and technological capabilities. Determine the optimal delivery route, evaluating options like AI Studio, company products, or transformation services. Maintain the outcome thread through delivery, validating decisions and ensuring alignment with intended value. Capture field feedback and lessons learned to contribute to internal IP and continuous improvement of methodologies. Provide mentorship and knowledge sharing to FDE Candidates and delivery practitioners.

Possess strong domain awareness, understanding customer workflows, value drivers, and industry context. Demonstrate robust technical credibility across enterprise solution architecture, engineering practices, data, integration, and cloud platforms. Apply a deep understanding of artificial intelligence, generative AI, agentic systems, RAG, and related emerging technologies. Exhibit a solid grasp of production AI considerations, including evaluation, security, privacy, Responsible AI, and operational readiness. Showcase strong client emotional intelligence, consulting, stakeholder management, and communication skills. Excel in analytical, problem-solving, critical-thinking, and evidence-based decision-making. Hold deep working expertise in a relevant specialist area such as AI engineering, architecture, data, or AI infrastructure. Maintain broad knowledge of relevant company and partner platforms, products, and accelerators. Demonstrate the ability to quickly learn and apply domain context, including processes, regulations, and business metrics. Exhibit commercial awareness to connect technical choices with business value, risk, and cost. Possess strong outcome leadership capabilities, driving clear decisions and prioritizing evidence. Maintain a strong reuse and product-feedback mindset. Communicate complex concepts clearly to diverse stakeholders. Ability to work independently, manage ambiguity, challenge constructively, and balance priorities. Influence technical and non-technical stakeholders across multiple organizational levels. Foster strong collaboration, relationship-building, and knowledge-sharing skills.