Join NTT DATA as a Senior AI Architect specializing in Manufacturing. This role is pivotal in driving manufacturing transformation through cutting-edge cloud, data, and AI solutions. You will architect scalable and secure platforms across shop floor operations, supply chain, and quality management.

Leverage your expertise to define reusable patterns for smart factories, predictive maintenance, and AI-driven insights. This is an opportunity to shape the future of manufacturing technology within a leading global organization.

NTT DATA is a dynamic and forward-thinking company committed to client success and societal impact. As a global leader in AI and digital infrastructure, we offer unparalleled capabilities and a supportive environment for innovation and growth.

Own the business and technology architecture for manufacturing transformation initiatives. Translate manufacturing strategies into robust cloud, data, AI, and agentic AI architectures. Define patterns for smart factories, predictive maintenance, quality analytics, and supply chain control towers.

Advise on plant modernization, asset performance, and supply chain optimization. Provide architectural guidance for Azure and AWS solutions, focusing on data platforms, IoT, edge, APIs, and microservices. Guide secure OT/IT integration across various manufacturing systems.

Identify and shape AI use cases for manufacturing, such as maintenance copilots and production planning agents. Understand and guide the application of RAG, vector search, and responsible AI practices. Lead workshops with diverse stakeholders and provide architectural oversight through reference architectures and governance forums.

Requires 13+ years in technology/consulting, with at least 5 years in architecture and 5 years in manufacturing domain programs. Deep knowledge of discrete, process, or hybrid manufacturing, Industry 4.0, ISA-95, OEE, quality, maintenance, and supply chain operations is essential.

Must have hands-on architectural depth in Azure and AWS, with practical familiarity in GCP, hybrid cloud, and associated services. Strong command of cloud-native patterns, including containers, serverless, APIs, events, lakehouse, streaming, edge/IoT, and integration platforms.

Possess strong AI and agentic AI architecture know-how, including LLMs, RAG, multi-agent orchestration, vector databases, LLMOps/GenAIOps, guardrails, and model risk management. Ability to translate business outcomes into target architectures and roadmaps is key. Excellent English communication skills are required for effective collaboration with international teams.