Azure Ai Architect Job In Ltimindtree Limited
- LTIMindtree
- 12 to 16 Yrs
- Bengaluru
- 4 months ago
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Job Description
- Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or equivalent experience.}
- Proven experience as an Azure Architect with a focus on AI solutions; strong background in Azure Machine Learning, Cognitive Services, and Azure Open AI.
- 5+ years of hands-on experience building, deploying, and managing AI applications on Microsoft Azure.
- Strong knowledge of Azure services, including Private Endpoint, Network Security, Virtual Networks, and IAM.
- Strong knowledge of machine learning principles, NLP, and data science; familiarity with large language models is a plus.
- Demonstrated experience with CI/CD processes, containers, and Azure DevOps.
- Proficiency in scripting and programming languages, such as Python, C#, or Java.
- Strong understanding of data security, privacy, and regulatory requirements in AI applications.
- Strong problem-solving skills, analytical mindset, and attention to detail.
- Excellent communication and interpersonal skills to effectively collaborate with technical and non-technical stakeholders.
- Ability to work autonomously, manage multiple projects, and prioritize effectively.
- Experience working with multi-cloud or hybrid-cloud environments.
- Familiarity with chatbot infrastructure and machine learning services.
- Azure Solutions Architect Expert or Azure Infrastructure Engineer certification is a plus.
Position Overview
We are seeking an experienced Azure Infrastructure Architect to design, implement, and manage scalable, secure, and high-performance infrastructure solutions using Microsoft Azure services. The ideal candidate will have strong expertise in Azure infrastructure, including virtual networks, virtual machines, security, and DevOps practices. You will collaborate with cross-functional teams to support infrastructure for AI-driven applications, chatbots, and global market rollouts.
Key Responsibilities:
1. Infrastructure Setup:
Design and implement Azure infrastructure resources including Virtual Networks (VNets), Virtual Machines (VMs), Azure Key Vault, Azure Web App, Azure Search Service, Redis Service, Storage Accounts + Azure Container Registry (ACR), and Machine Learning Workspace.
Deploy and manage OpenAI resources and ensure integration with AI and chatbot services.
Create and test chatbots via VMs for the US region to support AI applications.
Provision development (DEV), staging (STG), and production (PROD) resources in the US East region.
Manage network configurations across DEV, STG, and PROD environments.
2. Deployment & Rollout:
Develop and optimize CI/CD pipelines using Azure DevOps.
Automate deployment processes to streamline infrastructure delivery.
Restructure infrastructure into Bicep templates for market-specific conditions.
Configure environments across different regions and implement VNet peering globally.
Plan, execute, and monitor deployment strategies for the US market, including phased and big-bang rollouts.
Prepare and maintain escalation plans to ensure smooth operations.
3. Integration and Deployment & Testing
Conduct performance tests for Azure resources and applications.
Implement Azure Monitor, Log Analytics, and set up alerts and dashboards for real-time infrastructure performance tracking.
Conduct regular health checks and data migration/integration tasks for Cosmos DB.
Collaborate with developers and DevOps engineers to fine-tune infrastructure for optimal performance.
Deploy Infrastructure as Code (IaC) on Azure using Azure Resource Manager (ARM) or Bicep templates to define and manage the required infrastructure for solutions.
4. Security and Compliance:
Ensure that all Azure-based AI architectures comply with industry standards and best practices for security, data privacy, and regulatory compliance.
Design, implement, and manage security controls for Azure resources, including Virtual Networks (VNet), Private Endpoints, Network Security Groups (NSG), and Identity and Access Management (IAM), to ensure a robust and secure cloud environment.
5. Technical Collaboration and Client Interaction:
Serve as a subject matter expert in Azure AI technologies, providing guidance and best practices to internal teams and clients.
Engage directly with clients to understand business needs and translate them into technically feasible AI solutions on Azure.
Conduct technical training sessions and knowledge transfer workshops to enhance team and client understanding of Azure AI capabilities.
Required Qualifications:
Key Competencies:
Preferred Skills:
Employement Category:
Employement Type: Full timeIndustry: IT Services & ConsultingRole Category: IT Operations / EDP / MISFunctional Area: Not SpecifiedRole/Responsibilies: Azure Ai Architect Job In Ltimindtree LimitedContact Details:
Company: LTIMindtreeLocation(s): Bengaluru
Keyskills: azure devops python learning open azure ai architect machine
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LTIMindtree
[NSE: LTIMindtree] is a global technology consulting and digital solutions LTIMindtree company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 ...
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