Sr. AI Architect

NTT DATA BUSINESS SOLUTIONS; Bengaluru; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Bengaluru, India, is seeking a Sr. AI Architect to lead manufacturing-focused cloud, data, and AI architectures. You will shape patterns for smart factories, predictive maintenance, and digital twins, collaborating with global teams and clients across CET/IST overlap.

The role emphasizes advanced Azure/AWS architecture, data platforms, IoT, and AI governance, with emphasis on scalable, secure solutions and stakeholder workshops.

Qualifications

• 13+ years in technology/consulting with architecture focus.
• Deep manufacturing knowledge across plan, source, make, deliver, maintain.
• Hands-on Azure and AWS; working familiarity with GCP and hybrid cloud.
• Strong AI/agentic AI architecture know-how: LLMs, RAG, multi-agent orchestration.
• Translate business outcomes into target architecture, roadmaps and delivery backlog.

Responsibilities

• Demonstrate manufacturing capability knowledge to shape current/target state maps.
• Advise on smart factories, plant modernization, predictive maintenance and quality analytics.
• Provide architecture guidance for Azure/AWS solutions covering data, APIs, events, security and FinOps.
• Define secure OT/IT integration patterns across ERP/MES/QMS/SCADA environments.
• Identify AI/agentic use cases such as maintenance copilots and production planning agents.
• Lead workshops with stakeholders across India and Europe; drive governance forums.

Skills

AI architecture

Cloud architecture

Manufacturing domain knowledge

LLMs / GenAI

Agentic AI / multi-agent orchestration

RAG / vector search

Tools

Azure

AWS

GCP

IoT edge

Data integration

Security & governance

Power BI

Job description

Job Summary

Req ID: phone_number

We are currently seeking a Sr. AI Architect to join our team in Bangalore, Karnataka (IN-KA), India (IN).

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 (but any location is Fine) 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

• 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.

Requirements

• 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 skills Azure

• 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

• 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, GenAI and agents
• Amazon Bedrock for foundation models and agents
• Amazon SageMaker AI for model build/train/deploy and MLOps
• Computer vision / anomaly detection use cases at edge
• Semantic search and governed data access for RAG
• Agentic workflows for maintenance, supply chain, quality and engineering Strong / Working / Awareness / Gap
• IAM, KMS, Secrets Manager and network segmentation
• VPC, PrivateLink, hybrid networking and landing zones
• CloudWatch, CloudTrail and Config monitoring
• Policy-based access, data lineage and cross-domain governance Strong / Working / Awareness / Gap

Preferred Qualifications

• Azure Solutions Architect Expert
• AWS Solutions Architect Professional
• Google Professional Cloud Architect
• TOGAF/Business Architecture and exposure to ISA/IEC 62443 or industrial cybersecurity
• MBA, Industrial Engineering or Operations background is useful.