Job Summary

• Design and lead end‑to‑end agentic AI architectures for enterprise‑scale GenAI solutions.
• Architect and implement multi‑agent systems using frameworks such as LangChain, LangGraph, and Google ADK.
• Drive advanced RAG architectures, including chunking strategies, retrieval optimization, and grounding techniques.
• Own LLM strategy and model selection, balancing accuracy, cost, latency, and compliance.
• Develop high‑performance Python systems with strong system design and scalability principles.
• Optimize and manage vector databases for large‑scale semantic search and retrieval workloads.
• Lead advanced prompt engineering and orchestration patterns for complex agent workflows.
• Design API‑first, microservices‑based architectures for AI platforms and integrations.
• Implement LLM evaluation frameworks to measure quality, reliability, and drift.
• Ensure Security, Responsible AI, and governance standards are embedded across solutions.

Key Responsibilities

1. To architect| design and develop (through Team) solution for product/project & sustenance delivery
2. To support as an SME
3. To ensure knowledge up-gradation and work with new technologies so that the solution is current and meets quality standards and the client requirements
4. To train and develop team so as to ensure that there is an adequate supply of trained manpower in the said technology and deliver risks are mitigated
5. To gather specifications and deliver solutions to the client organization based on understanding of a domain or technology
6. To review project deliverables.
7. To recommend client value creation initiatives and implement industry best practices (on specific technology/product)

Skill Requirements

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Other Requirements

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