Agent AI Architect

Tata Consultancy Services; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Tata Consultancy Services is seeking a senior AI architecture leader to design and govern end-to-end Agentic AI platforms and multi-agent ecosystems. The role emphasizes scalable, secure cloud-native architectures with governance across complex environments.

You will drive orchestration, memory, planning and tool integration patterns, shaping technical decisions and guiding cross-functional teams through architecture reviews and stakeholder discussions.

Qualifications

• 10–15 years of architecture or senior engineering experience with AI focus.
• Expertise in multi-agent architecture, orchestration and knowledge graphs.
• Hands-on knowledge of Google ADK, Vertex AI, Gemini and GCP services.
• Experience with LangGraph, LangChain, AutoGen, CrewAI and microservices architecture.
• Ability to define secure, scalable production architectures with governance.

Responsibilities

• Architect end-to-end Agentic AI platforms and multi-agent ecosystems.
• Define orchestration, reasoning, memory, planning, RAG, MCP and tool integration patterns.
• Design secure cloud-native solutions using Vertex AI, Cloud Run, GKE, Spanner and Vector Search.
• Establish AI governance, guardrails, observability, security, compliance and cost controls.
• Translate business requirements into architecture and design documentation.
• Lead architecture reviews and stakeholder discussions across teams.

Skills

AI solution architecture

Multi-agent architecture

LLMs & RAG

Vertex AI

GCP services

Tools

Google ADK

LangGraph

LangChain

AutoGen

CrewAI

Job description

Job Description:

Key Responsibilities

• Architect end-to-end Agentic AI platforms and multi-agent ecosystems.
• Define orchestration, reasoning, memory, planning, RAG, MCP and tool-integration patterns.
• Design secure cloud-native solutions using Vertex AI, Cloud Run, GKE, Cloud Spanner and Vector Search.
• Establish AI governance, guardrails, observability, security, compliance and cost controls.
• Translate business requirements into architecture and design-ready documentation.
• Lead architecture reviews, technical decisions and stakeholder discussions across business and engineering teams.

Required Skills & Experience

• 10–15 years of architecture or senior engineering experience, including strong AI solution architecture exposure.
• Expertise in multi-agent architecture, agent orchestration, LLMs, RAG, grounding, MCP and knowledge graphs.
• Hands-on knowledge of Google ADK, Vertex AI, Gemini and GCP services.
• Experience with LangGraph, LangChain, AutoGen, CrewAI and microservices architecture.
• Strong ability to define secure, scalable and governed production architectures.