Enterprise Infrastructure & Cloud Architect

Tata Consultancy Services; Chennai District, Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Tata Consultancy Services is seeking an experienced Enterprise Infrastructure & Cloud Architect GenAI / Agentic AI Specialist to design enterprise-scale cloud and AI platforms across Azure and GCP. You will lead GenAI initiatives, architect AI copilots and autonomous agents, and drive cloud modernization.

Collaborating with stakeholders, you will establish AI governance, security, and cost-optimization while mentoring teams and advancing DevOps, MLOps, and AI deployment lifecycles.

Qualifications

• Bachelor's or Master's degree in CS/IT/Engineering or related field.
• 10-15 years of experience in enterprise cloud/infrastructure and AI architectures.

Responsibilities

• Design and architect enterprise-scale cloud and AI solutions across Azure and GCP.

Skills

GenAI Architecture

Cloud Strategy

Azure & GCP

Kubernetes

Docker

Infrastructure as Code

Security & Governance

MLOps

DevOps & CI/CD

Technical Leadership

Education

Bachelor's or Master's in Computer Science / IT / Engineering

Tools

Terraform

Kubeflow

CI/CD tooling

LLM frameworks

Job description

Job Title: Enterprise Infrastructure & Cloud Architect GenAI / Agentic AI Specialist

Experience: 10-15 Years

Location: Hyderabad, Chennai

Key Responsibilities:

• Design and architect enterprise-scale cloud and AI solutions across Azure and GCP.
• Develop and implement GenAI and Agentic AI platforms using LLMs, RAG, and multi-agent frameworks.
• Lead cloud modernization, infrastructure transformation, and AI adoption initiatives.
• Architect AI copilots, autonomous agents, and intelligent automation solutions for business processes.
• Establish secure, scalable, and resilient cloud infrastructure using Kubernetes, Docker, and Infrastructure-as-Code.
• Define AI governance, security, compliance, and responsible AI frameworks.
• Collaborate with business stakeholders, enterprise architects, and engineering teams to translate business requirements into technical solutions.
• Provide technical leadership, architecture reviews, and best practices for AI and cloud implementations.
• Drive DevOps, CI/CD, and MLOps practices for AI application deployment and lifecycle management.
• Evaluate emerging AI, cloud, and infrastructure technologies and recommend strategic adoption.
• Mentor technical teams and support enterprise-wide AI transformation programs.
• Ensure performance, reliability, scalability, and cost optimization of cloud and AI platforms.

Educational Qualification

• Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering, or related discipline.