AI Architect
Posted 18 Sep 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 12+ yrs
- Management level
- Individual contributor
No salary listed for this role.
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a AI Architect to join our team in Noida / Gurgaon, Delhi (IN-DL), India (IN).
AI Architect:
Required skills
• 12+ years of experience in software engineering, enterprise architecture, solution architecture, platform architecture, or senior technical leadership roles.
• Strong cumulative technical knowledge across AI/ML, LLMs, agentic systems, software engineering, cloud platforms, distributed systems, data architecture, APIs, DevOps, and security.
• Strong hands-on understanding of Python for AI engineering, automation, orchestration, and AI service development.
• Strong hands-on understanding of C#, .NET and enterprise backend application architecture.
• Strong SQL expertise and understanding of relational databases, data modeling, query optimization, and enterprise data access patterns.
• Proven experience designing enterprise-scale platforms or applications in complex, data-intensive environments.
• Experience architecting LLM-based applications, AI agents, RAG systems, workflow automation, and intelligent decision-support solutions.
• Experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, Google ADK, or similar frameworks.
• Strong understanding of MCP server architecture and how AI systems integrate with enterprise APIs, tools, repositories, and data platforms.
• Experience with cloud-native architecture on AWS, Azure, or Google Cloud.
• Strong knowledge of microservices, APIs, event-driven architecture, containers, CI/CD, infrastructure-as-code, observability, and production operations.
Preferred skills:
• Experience in financial services, capital markets, ratings, risk analytics, commodities, fintech, or regulated enterprise environments.
• Experience with AWS services such as EC2, ECS, Lambda, RDS, API Gateway, SageMaker, Bedrock, CloudFormation, CDK, or comparable cloud services.
• Experience with vector databases such as OpenSearch, FAISS, Pinecone, or pgvector.
• Experience with AI governance, model lifecycle management, responsible AI, model risk controls, data privacy, and auditability.