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AI Architect

TATA Consultancy Services LimitedAtlanta, GA🇺🇸United StatesPosted 29 Jul 2026

Quick Overview

Work Type

Hybrid

Level

Mid Senior

Job Description

Must Have Technical/Functional Skills

Hands‑On Development & POCs
Build rapid POCs demonstrating:
Multi-agent collaboration
Autonomous task execution
Agents interacting with client’s APIs, data platforms, and operational systems
MCP‑based tool integrations for internal systems
Develop reference implementations using:
Vertex AI Agent Builder
Gemini models
GPT‑based agents
Google Cloud Platform AI Agentic capabilities (If not, Azure AI Agentic capabilities is fine)
Create debugging, observability, and evaluation frameworks for agent behavior.

Roles & Responsibilities

Agentic AI Strategy & Architecture

Define client’s Agentic AI vision, including multi-agent patterns, orchestration models, and enterprise integration strategy.

Lead architecture for:

A2A (Agent‑to‑Agent) protocol–based systems
MCP servers and tool providers
Agent orchestration frameworks (e.g., LangChain, LlamaIndex, Vertex AI Agents)
Tool‑calling and function‑calling ecosystems
Establish reusable patterns for agent autonomy, delegation, memory, and safety.

Enterprise Integration

Integrate agentic systems with client’s:

Google Cloud Platform data ecosystem (BigQuery, Pub/Sub, Cloud Run)
APIs, microservices, and event-driven systems
Identity, security, and governance frameworks
Define standards for agent safety, guardrails, and responsible autonomy.

Client Engagement & Sales Influence

Drive AI/Agentic use case discovery with client’s business and technology leaders.
Shape proposals, solution narratives, and executive presentations.
Act as the primary AI/Agentic technical advisor for the client’s account.

Cross‑Functional Leadership

Partner with cloud, data engineering, product, and business teams to deliver cohesive solutions.
Mentor engineers on agentic patterns, tool integration, and modern AI development

Skills

Microservices

Azure

BigQuery

GPT

Google Cloud

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