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Agentic Ai Lead

NTT DATA, Inc.
Posted on
NTT DATA, Inc. logo

Experience
7 - 11 yrs
Job Location
Hyderabad, India
Vacancy
2
Designation
Lead Data Scientist
Job Type
Not specified

Job Description

Agentic AI & Enterprise AI Development
  • Design and implement Agentic AI systems using modern orchestration frameworks.
  • Build autonomous and semi-autonomous AI agents capable of reasoning, planning, and tool use.
  • Design and optimize RAG architectures and enterprise knowledge retrieval systems.
  • Develop enterprise copilots utilizing Microsoft Copilot, Azure OpenAI, Claude, and other LLM ecosystems.
  • Implement multi-agent coordination architectures and workflow automation.
MCP (Model Context Protocol)
  • Design and integrate MCP-based solutions.
  • Build custom MCP servers and connectors.
  • Develop integrations across enterprise applications, databases, APIs, and collaboration platforms.
  • Implement secure context management and tool orchestration.
AI-Assisted SDLC & Spec-Driven Development
  • Lead AI-assisted software development practices across the SDLC.
  • Implement Spec-Driven Development methodologies.
  • Utilize Copilot, Claude Code, Cursor, and AI-assisted engineering tools.
  • Establish AI-assisted testing, documentation, code review, and deployment frameworks.
  • Define engineering standards for AI-native software delivery.
Data Governance & Lineage
  • Develop enterprise data governance frameworks.
  • Implement data quality, metadata management, and lineage tracking solutions.
  • Ensure compliance with security, privacy, regulatory, and responsible AI requirements.
  • Integrate governance capabilities across data and AI ecosystems.
Enterprise Architecture & Deployment
  • Architect scalable AI solutions on Azure/AWS/GCP.
  • Design API-driven and event-driven AI infrastructures.
  • Integrate AI services with enterprise platforms such as Microsoft 365, ServiceNow, Salesforce, SAP, and internal systems.
  • Optimize AI system reliability, observability, and scalability.
Stakeholder Engagement
  • Engage directly with business leaders, product teams, architects, and customers.
  • Conduct solution workshops and architecture reviews.
  • Translate business challenges into measurable AI outcomes.
  • Provide technical leadership and mentorship.

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