AI & Generative AI Architect (Azure Cloud)
7 days ago
Position Overview
We are seeking an experienced AI & Generative AI Architect with deep expertise in Azure Cloud services to design, develop, and implement cutting-edge AI solutions. The ideal candidate will have a strong background in artificial intelligence, machine learning, and generative AI technologies, combined with extensive hands-on experience with Microsoft Azure cloud platform.
Required QualificationsExperience
- *Minimum 8+ years* of overall experience in software development, data engineering, or AI/ML roles
*Minimum 5+ years* of hands-on experience with Microsoft Azure cloud platform
*3+ years* of experience in AI/ML architecture and implementation
*2+ years* of experience with Generative AI technologies and Large Language Models (LLMs)
*Azure Cloud Services:*
Azure Machine Learning, Azure OpenAI Service, Azure Cognitive Services
Azure Databricks, Azure Synapse Analytics, Azure Data Factory
Azure Kubernetes Service (AKS), Azure Container Registry
Azure Functions, Logic Apps, and Event Grid
Azure Storage solutions (Blob, Data Lake Gen2)
Azure networking, security, and identity management (Azure AD, Key Vault)
*AI & Machine Learning:*
- Deep understanding of machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch)
Experience with MLOps practices and model lifecycle management
Expertise in building and deploying AI models at scale
Knowledge of computer vision, NLP, and predictive analytics
*Generative AI:*
Hands-on experience with Large Language Models (GPT-4, Claude, Llama, etc.)
Experience with Azure OpenAI Service and prompt engineering
Knowledge of RAG (Retrieval Augmented Generation) architecture
Fine-tuning and customization of foundation models
Vector databases and semantic search (Azure AI Search, Pinecone, Weaviate)
LangChain, Semantic Kernel, or similar frameworks
*Programming & Development:*
Strong proficiency in Python and SQL
Experience with REST APIs and microservices architecture
Knowledge of CI/CD pipelines (Azure DevOps, GitHub Actions)
- Infrastructure as Code (Terraform, ARM templates, Bicep)
Architecture & Design
Design end-to-end AI and GenAI solutions on Azure cloud platform aligned with business objectives
Define reference architectures, design patterns, and best practices for AI/ML implementations
Create scalable, secure, and cost-effective cloud architectures for AI workloads
Evaluate and recommend appropriate Azure AI services and tools for specific use cases
Lead the development and deployment of AI/ML models and GenAI applications
Implement MLOps pipelines for continuous training, testing, and deployment
Build RAG systems and intelligent agents using LLMs and Azure services
-Optimize model performance, latency, and cost efficiency
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