AI Engineer - Agentic AI & Multi-Agent Systems_XP 6+_PAN INDIA

Tata Consultancy Services Limited; India; Sur place; INR 2 500 000 - 4 500 000; Plein temps

Résumé du poste

Tata Consultancy Services Limited is seeking an experienced AI Engineer to design, develop, and deploy enterprise-scale Agentic AI, Multi-Agent Systems, and GenAI solutions on Google Cloud Platform. Build production-ready AI applications, integrate enterprise systems, and ensure scalability, security, and operational excellence.

The role requires hands-on expertise in Vertex AI, Gemini, and LLMOps, with a strong focus on CI/CD, observability, and governance across large-scale deployments.

Qualifications

• Design and implement Agentic AI and Multi-Agent solutions.
• Develop GenAI applications using Vertex AI and Gemini.
• Build scalable RAG architectures and enterprise integrations.
• Deploy and manage AI workloads on GCP.
• Implement AI security, governance, and observability.

Responsabilités

• Design and implement Agentic AI and Multi-Agent solutions.
• Develop GenAI applications using Vertex AI and Gemini.
• Build scalable RAG architectures and enterprise integrations.
• Deploy and manage AI workloads on GCP.
• Implement AI security, governance, and observability.
• Drive CI/CD, LLMOps, and production support practices.

Connaissances

Agentic AI

Multi-Agent Systems

Generative AI

Vertex AI

Python

Gemini

RAG

GCP

FastAPI

Kubernetes

Terraform

LLMOps

Description du poste

AI Engineer - Agentic AI & Multi-Agent Systems

Notice Period: Preferably less than 30 Days

Location: PAN India (Hybrid)
Experience: 10-12 Years
Employment Type: Full-Time

Job Summary

We are looking for an experienced AI Engineer to design, develop, and deploy enterprise-scale Agentic AI, Multi-Agent Systems, and Generative AI solutions on Google Cloud Platform. The role involves building production-ready AI applications, integrating enterprise systems, implementing RAG architectures, and ensuring scalability, security, and operational excellence.

Key Skills

• Agentic AI


• Multi-Agent Systems


• Generative AI


• Vertex AI


• Python


• Gemini


• RAG (Retrieval-Augmented Generation)


• Google Cloud Platform (GCP)


• FastAPI


• Kubernetes


• Terraform


• LLMOps

Responsibilities

• Design and implement Agentic AI and Multi-Agent solutions.


• Develop GenAI applications using Vertex AI and Gemini.


• Build scalable RAG architectures and enterprise integrations.


• Deploy and manage AI workloads on GCP.


• Implement AI security, governance, and observability.


• Drive CI/CD, LLMOps, and production support practices.