Description

• Design and implement end-to-end cloud architectures leveraging Azure services including:
  • Azure Blob Storage
  • Azure Data Lake Storage (ADLS)
  • Azure Functions
  • Azure App Services/Web Apps
  • Azure SQL Database
  • Azure Kubernetes Service (AKS)
  • Azure OpenAI Service
• Architect scalable data and AI platforms using:
  • Azure Machine Learning (Azure ML)
  • Azure Databricks
  • Azure OpenAI
  • Modern cloud-native architecture patterns
• Design and implement Generative AI solutions, including:
  • Retrieval-Augmented Generation (RAG) architectures
  • Vector databases and semantic search
  • Prompt engineering frameworks
  • LLM orchestration and AI integration strategies
• Build secure, enterprise-grade solutions utilizing:
  • Azure Key Vault
  • Azure Container Registry (ACR)
  • Microsoft Entra ID (Azure AD)
  • Security, governance, and compliance best practices
• Collaborate with business stakeholders, engineering teams, and solution leaders to:
  • Define technical roadmaps
  • Establish architecture standards and solution patterns
  • Drive integration strategies
  • Design deployment and operational frameworks
• Lead containerization and orchestration initiatives using:
  • Docker
  • Kubernetes
  • Azure Kubernetes Service (AKS)
• Provide technical leadership in:
  • Architecture reviews
  • Performance tuning and optimization
  • DevOps and CI/CD enablement
  • Cost optimization initiatives
  • Cloud migration and modernization programs

Qualifications:

• 7–9 years of overall experience in cloud architecture, solution design, or data engineering.
• Strong expertise in Microsoft Azure cloud services and solution architecture.
• Hands-on experience with Azure OpenAI and AI-powered application development.
• Strong understanding of Generative AI concepts, Large Language Models (LLMs), and RAG frameworks.
• Experience building scalable data platforms using Azure Databricks and Azure ML.
• Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes, AKS).
• Experience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, or related tooling.
• Strong knowledge of cloud security, governance, networking, and identity management.
• Experience in designing high-availability, fault-tolerant, and enterprise-scale solutions.
• Excellent stakeholder management and communication skills.

Preferred Qualifications

• Microsoft Azure Certifications (Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent).
• Experience working with enterprise AI transformation initiatives.
• Exposure to MLOps, LLMOps, and AI governance frameworks.
• Experience with vector databases, Cognitive Search/Azure AI Search, and knowledge management solutions.

Interview Focus Areas
Candidates should be able to demonstrate expertise in:

• Azure AI Services and Azure OpenAI
• RAG (Retrieval-Augmented Generation) architectures
• Azure cloud architecture and design patterns
• Azure Databricks and Azure ML
• AKS and Kubernetes
• CI/CD and DevOps practices
• Security, governance, and scalability best practices

Key Skills

Education

Bachelor's degree