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AI Tech Lead / AI Architect

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NTT DATA

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Location:
India , Bangalore

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

The AI Tech Lead / Architect will design and implement enterprise-grade AI solutions, focusing on multi-agent systems and workflow orchestration. Candidates should have over 7 years of experience in software engineering and at least 2 years in AI solutions. Strong skills in Python and AI reasoning systems are essential. This role requires collaboration with various teams to ensure compliance and operational readiness.

Job Responsibility:

  • Multi-agent architecture & workflow orchestration: Define how agents work together (roles, shared context, coordination) and design orchestrated agent workflows for real business processes
  • Reusable patterns (avoid one-offs): Establish standard reference patterns and starter implementations so teams don’t build bespoke, hard-to-maintain AI solutions
  • Governance & compliance built-in: Embed practical controls (human-in-the-loop, approvals where needed) and ensure privacy/security expectations are met for sensitive/client data
  • Observability & production readiness: Ensure solutions have monitoring/telemetry and meet production standards for reliability and operational support
  • Enterprise integration & access control: Integrate agents with enterprise platforms/data sources and enforce entitlements/least-privilege access to prevent unintended exposure
  • Technical leadership & translation: Guide engineering teams, act as SME, and translate business objectives into scalable AI architecture that delivers measurable outcomes

Requirements:

  • 7+ years software engineering/architecture experience
  • 2+ years delivering AI/GenAI/ Agentic AI solutions in production
  • Strong architecture skills: distributed services, APIs, integration, security, and reliability
  • Hands-on experience with RAG and agentic/workflow orchestration patterns
  • Strong understanding of multi-agent systems, agent orchestration, and coordination patterns
  • Experience working with LLMs or AI reasoning systems, including managing model limitations and risks
  • Solid background in enterprise software engineering, APIs, and system integration
  • Strong understanding of Agentic AI Cognitive Frameworks
  • Strong understanding of Architectural Components of Agentic AI systems
  • Python, production-grade engineering practices
  • RAG: embeddings, vector stores, retrieval + grounding, evaluation
  • Agentic frameworks (workflow/tool orchestration patterns)
  • MCP servers and AI tool integration experience
  • Observability/quality controls for AI solutions (monitoring + operational readiness)
  • Familiarity with Copilot/coding assistants in dev workflows

Additional Information:

Job Posted:
March 13, 2026

Work Type:
On-site work
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