AI Architect

Key Responsibilities

Application Modernization & Cloud Transformation Assess and modernize legacy applications using cloud-native architecture patterns.

Design and implement scalable solutions using Azure PaaS services and Gemini Enterprise for CX Lead migration of on-premises applications and services to Microsoft Azure.

Transform monolithic applications into microservices and API-driven architectures.

Develop modernization roadmaps aligned to business goals and customer experience objectives.

Establish architectural standards, governance, security, and operational best practices.

Experience with Azure and GCP Cloud Platforms Architect resilient, scalable, and highly available solutions on Azure.

Design enterprise cloud platforms leveraging Azure App Services, AKS, Azure Functions, API Management, Azure SQL, Cosmos DB, and Integration Services.

Implement Infrastructure as Code using Terraform and Bicep.

Drive cloud adoption strategies focused on reliability, security, cost optimization, and performance.

AI & Generative AI Solutions

Design and implement AI-enabled business capabilities using Gemini Enterprise for CX, Azure AI Services and Azure OpenAI.

Develop Generative AI solutions including enterprise copilots, intelligent assistants, document intelligence, and knowledge management systems.

Leverage Azure AI Search, vector databases, Semantic Kernel, and Retrieval-Augmented Generation (RAG) architectures.

Establish AI governance, responsible AI frameworks, security controls, and monitoring standards.

Identify opportunities to improve customer and employee experiences through AI-powered automation and insights.

Integration & Data Architecture

Design enterprise integration solutions using Azure API Management, Logic Apps, Service Bus, Event Grid, and Event Hubs.

Enable hybrid connectivity between on-premises and cloud platforms.

Architect real-time and batch synchronization solutions across enterprise applications.

Design modern data architectures leveraging Azure SQL, Cosmos DB, Microsoft Fabric, Azure Synapse, and Azure Data Factory.

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DevSecOps & Platform Engineering

Establish CI/CD pipelines using Azure DevOps and GitHub Actions.

Embed security and compliance controls throughout the software development lifecycle.

Implement monitoring and observability solutions using Azure Monitor, Log Analytics, and Application Insights.

Promote DevSecOps, SRE, and platform engineering best practices.

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Required Qualifications

Experience

10+ years of experience in software engineering, architecture, and enterprise application delivery.

5+ years of hands-on Azure/Google cloud architecture experience.

3+ years of experience designing and implementing AI/Generative AI solutions.

Proven success leading large-scale application modernization and cloud transformation initiatives.

Experience delivering customer-facing digital platforms and enterprise integration solutions.