AI Architect

Role overview

AI Architect at Zensar

AI Strategy & Architecture Define enterprise AI architecture roadmap aligned with business and technology objectives.

Experience 12-18+ Years in Enterprise Infrastructure, Cloud Architecture, AI/ML Platforms, Automation, and Digital Transformation Role Summary We are seeking an experienced AI Architect to lead the design and implementation of AI-driven solutions across enterprise cloud and infrastructure environments.

The ideal candidate should possess deep expertise in cloud architecture, enterprise infrastructure, AI technologies, automation platforms, and modern operational frameworks.

Responsibilities

• Design scalable AI/ML and Generative AI platforms across hybrid cloud environments.
• Establish AI governance, responsible AI practices, security, and compliance frameworks.
• Identify AI opportunities across IT Operations, Service Management, Security, Network, Cloud, and End User Computing.
• Cloud & Infrastructure Architecture Architect solutions across: Microsoft Azure AWS Google Cloud Platform (GCP) Design hybrid cloud and multi-cloud architectures.
• Define cloud landing zones, security baselines, identity integration, and operational frameworks.
• Modernize infrastructure through automation and AI-enabled operations.
• AI-Powered Infrastructure Operations Drive enterprise use cases such as: AIOps Predictive incident management Event correlation and noise reduction Root cause analysis automation Capacity forecasting Service health monitoring Network AI Automated network impact analysis SD-WAN optimization AI-assisted troubleshooting Network anomaly detection Security AI Threat detection and response Security event correlation AI-driven vulnerability prioritization Cyber risk analytics Workplace & End User Computing AI Virtual agent solutions AI-powered service desk Knowledge management automation Sentiment and experience analytics GenAI & Copilot Solutions Design enterprise GenAI platforms using: Azure OpenAI Microsoft Copilot AWS Bedrock Open-source LLMs Build Retrieval-Augmented Generation (RAG) architectures.
• Implement AI assistants and enterprise chatbots.
• Integrate AI solutions with ServiceNow, ITSM, CMDB, monitoring, and enterprise applications.
• Automation & Engineering Develop AI-driven automation using: Python PowerShell Terraform Ansible GitHub Enterprise DevOps platforms Design self-healing infrastructure frameworks.
• Build infrastructure-as-code and AI-assisted operational workflows.
• Stakeholder Management Collaborate with CIOs, CTOs, Infrastructure Leaders, Security Teams, and Business Stakeholders.
• Provide technical leadership for large transformation programs.
• Support pre-sales, solutioning, RFP responses, and technical governance.
• AI Architect – Enterprise Cloud & Infrastructure (Hybrid) Location - Hybrid (Pune) | Client & Enterprise Environment

Required qualifications

• 10 + Years

Employment details

• Shift: 24*7 Required Technical Skills AI & Data Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases AI Agents MLOps AI Governance Cloud Platforms Microsoft Azure AWS Google Cloud Platform Automation Python PowerShell Ansible Terraform GitHub Actions Azure DevOps Qualifications Education Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering, or related field.
• Preferred Certifications Microsoft Certified: Azure Solutions Architect Expert Microsoft Certified: Azure AI Engineer Associate AWS Solutions Architect Professional Google Professional Cloud Architect TOGAF CISSP (Preferred) ITIL Expert / Managing Professional Desired Experience 12+ years in Enterprise Infrastructure & Cloud. 5+ years in AI, Automation, AIOps, or Intelligent Operations.
• Experience architecting enterprise-scale solutions supporting 10,000+ users.
• Experience leading cloud transformation and AI adoption initiatives.
• Strong advisory and customer-facing consulting experience.
• Location: India

Additional role details

• The role will focus on integrating Generative AI, AIOps, automation, cloud platforms, and enterprise infrastructure services to improve operational efficiency, reliability, security, and business outcomes.