AI Architect
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 8, 2026. NTT DATA scores B on the Alion truth index.
India T&M Special Bonus:
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.
- Experience supporting SaaS modernization, platform transformation, operating model transformation, or enterprise architecture governance.
Agentic solution- who can build solution at architect levelLLMAI agentsRAG appPythonAWS CloudC#, .NetAdv SQL (hands on)Low level design-high level design.MCP Server architecture,Good to have - Capital Market experience
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