Google Data Architect

Tata Consultancy Services; Hyderabad; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

Tata Consultancy Services is seeking a senior architect to design end-to-end AI platforms and multi-agent ecosystems in a large enterprise environment.

You will lead orchestration, governance, and secure cloud-native solutions using Vertex AI and GCP services for scalable production architectures.

Qualifications

• 10–15 years of architecture or senior engineering experience, including 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.

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.

Skills

Multi-Agent Architecture

Agent Orchestration

LLMs

RAG

Grounding

MCP

Knowledge Graphs

Google ADK

Vertex AI

Gemini

LangGraph

Microservices

LangChain

AutoGen

CrewAI

Tools

Google ADK

Vertex AI

Gemini

GCP Services

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.

Key Skills

Multi-Agent Architecture, Agent Orchestration, LLM, RAG, Grounding, MCP, Knowledge Graphs, Google ADK, Vertex AI, Gemini, LangGraph, Microservices