Cloud Engineer

Job Description: Senior Azure AI Foundry Engineer Location: Dallas, Texas Position Type: Contract Work Mode: Hybrid Experience: 10+ Years Key Responsibilities • Architectural Leadership & Strategy: • Design, architect, and implement scalable, secure, and cost-effective AI solutions on the Azure AI Foundry platform. • Define the technical vision and reference architectures for generative AI applications, including RAG (Retrieval-Augmented Generation), multi-agent systems, and advanced fine-tuning strategies. • Evaluate and select the most appropriate Azure AI models (e.g., GPT-4, Llama 2, Phi-3) and services to meet business objectives. Required Qualifications & Experience • A minimum of 10 years of progressive experience in software development, data engineering, or ML engineering, with at least 3 years focused on building and deploying AI/ML solutions on Microsoft Azure. • Must-have hands-on experience with Azure AI Foundry and Azure AI Studio. • Deep, practical expertise in generative AI, including: • Advanced Prompt Engineering techniques. • Fine-tuning Large Language Models (LLMs). • Designing and implementing RAG (Retrieval-Augmented Generation) architectures. • Expert-level proficiency in Python and experience with AI/ML frameworks like LangChain, Semantic Kernel, PyTorch, or TensorFlow. • Proven experience in designing and implementing MLOps pipelines on Azure using Azure ML, Git, CI/CD tools (Azure DevOps/GitHub Actions), and model registries. • Strong experience with Azure data and storage services: Azure AI Search, Azure Blob Storage, Cosmos DB, and SQL Database. • Solid understanding of cloud infrastructure as code (IaC) using Terraform or Bicep. • Experience with containerization (Docker, Kubernetes) and deploying models to AKS. • Excellent problem-solving, analytical, and communication skills. Preferred Qualifications • Microsoft Certified: Azure AI Engineer Associate (AI-102) or higher. • Experience with other cloud AI platforms (AWS SageMaker, GCP Vertex AI) is a plus. • Knowledge of responsible AI principles, model fairness, interpretability, and security. • Previous experience in a technical leadership or principal engineer role.