AI Architect Lead Advisor

Make an impact with NTT DATA Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive. Business Domain Architect – Manufacturing Senior domain architect with 13+ years experience combining deep business domain expertise with cloud (AWS, Azure), data, AI and agentic AI architecture. Strong AWS & Azure Architecture experience with working knowledge in GCP. Locations: Bangalore/Pune/Delhi NCR/Chennai/Hyderabad Mode: Hybrid / client-facing    Primary cloud: Azure + AWS; GCP working knowledge    Domain focus: Smart manufacturing, OT/IT, supply chain ROLE PURPOSE: Own business and technology architecture for manufacturing transformation across shop floor, supply chain, quality, maintenance, engineering and aftermarket. Translate manufacturing strategy into scalable, secure and value-driven cloud, data, AI and agentic AI architectures. Define reusable patterns for smart factories, predictive maintenance, quality analytics, production optimization, supply chain control towers, digital thread, digital twins and agentic AI copilots KEY RESPONSIBILITIES    MUST-HAVE EXPERIENCE AND SKILLS •    Demonstrate strong knowledge of manufacturing capabilities across plan, source, make, deliver, maintain and service value streams, and use this knowledge to shape current-state and target-state capability maps. •    Advise on manufacturing transformation initiatives, including smart factories, plant modernization, asset performance, predictive maintenance, quality analytics and supply chain control towers. •    Provide manufacturing-domain architectural guidance for Azure and AWS solutions supporting data platforms, IoT and edge, APIs and events, microservices, security, reliability, observability and FinOps, without necessarily being responsible for hands-on engineering or platform configuration. •    Define and guide secure OT/IT integration patterns across ERP, MES, PLM, QMS, EAM, SCM, historian and time-series platforms, SCADA/PLC environments and industrial connectivity layers. •    Identify and shape AI and agentic AI use cases relevant to manufacturing, such as maintenance copilots, production-planning agents, root-cause analysis agents, supplier-risk assistants and enterprise knowledge search. •    Understand and guide the application of RAG, vector search, tool use, human-in-the-loop review, prompt and policy controls, evaluation, monitoring, responsible AI and data governance within manufacturing environments. •    Lead domain-focused workshops with plant operations, engineering, quality, supply chain, CIO, CTO and COO stakeholders, enterprise architects, delivery teams and vendors across India and Portugal. •    Provide architectural oversight through reference architectures, architecture decision records, non-functional requirements, risk reviews, vendor assessments and governance forums. •    Work closely with cloud, data, application, security, OT and AI engineering teams that are responsible for detailed design, development, configuration and implementation.     - 13+ years in technology/consulting, including 5+ years in architecture and 5+ years in manufacturing domain programs. - Deep manufacturing knowledge: discrete/process/hybrid manufacturing, Industry 4.0, ISA-95 concepts, OEE, quality, maintenance and supply chain operations. - Hands-on architecture depth in Azure and AWS; practical familiarity with GCP, hybrid cloud, identity, network, security, data and integration services. - Strong command of cloud-native patterns: container/serverless, APIs, events, lakehouse/warehouse, streaming, edge/IoT and integration platforms. - Good AI and agentic AI architecture know-how: LLMs, RAG, multi-agent orchestration, vector databases, LLMOps/GenAIOps, guardrails and model risk. - Ability to convert business outcomes into target architecture, transition states, investment roadmap and delivery backlog. - Excellent English communication; able to work with India and Europe teams with CET/IST overlap  Hyperscaler skill checklist Azure Capability Area    Candidate should know    Check Manufacturing platform & data    •    Microsoft Fabric / OneLake lakehouse for manufacturing data •    Azure Data Factory / Event Hubs / Stream Analytics patterns •    Azure Digital Twins / Fabric Digital Twin Builder concepts Power BI and Real-Time Intelligence for operational dashboards    Strong / Working / Awarenes / Gap IoT, edge and hybrid    •    Azure IoT Operations / IoT Hub / IoT Edge concepts •    Arc-enabled Kubernetes / hybrid management    Strong / Working / Awareness / Gap AI, agents and automation     •    Azure AI Foundry / Azure OpenAI / Foundry Local concepts •    Copilot Studio, Semantic Kernel, Azure Functions and Logic Apps integration •    RAG, agent orchestration, prompt/version control and evaluation •    Computer vision for quality and safety use cases •    Human approval, action policy and business workflow integration    Strong / Working / Awareness / Gap Security, governance and operations     •    Microsoft Entra ID, RBAC and managed identities •    Key Vault, Defender for Cloud, Sentinel, Azure Policy •    Purview for data governance, lineage and classification •    Azure Monitor / App Insights for observability    Strong / Working / Awareness / Gap AWS Capability Area    Candidate should know    Check Manufacturing platform & data    •    AWS IoT SiteWise / SiteWise Edge for industrial data •    S3 data lake, Glue Data Catalog, Lake Formation governance •    Amazon Timestream / Kinesis / Managed Flink for time-series and streaming    Strong / Working / Awarenes / Gap IoT, edge and hybrid    •    AWS IoT Core, Greengrass, Shop Floor Connectivity Framework •    Industrial protocol ingestion with partner connectors    Strong / Working / Awareness / Gap AI,