AI Engineer (Azure)

We are seeking a skilled AI Engineer with strong hands-on experience in Azure AI and Machine Learning services. The ideal candidate will design, develop, and deploy scalable AI/ML and Generative AI solutions leveraging Azure Cloud technologies, Microsoft Fabric, and Azure AI Foundry to solve complex business challenges and drive innovation.

Key Responsibilities

• Design, develop, and deploy AI/ML models using Azure Machine Learning, Azure Databricks, and Microsoft Fabric.
• Build and operationalize LLM-based solutions leveraging Azure AI Foundry, Azure OpenAI, and Cognitive Services.
• Implement RAG-based architectures using Azure AI Search, Vector Databases, and LangChain or LangGraph frameworks.
• Collaborate with Data Engineers and Architects to integrate AI applications with Microsoft Fabric datasets ensuring governance, data lineage, and reliability.
• Implement MLOps and LLMOps best practices for continuous integration, delivery, and monitoring of AI models using Azure ML Pipelines and Azure DevOps.
• Optimize model performance and ensure scalability, security, and reliability of deployed solutions.
• Work closely with business and technical stakeholders to translate requirements into AI-driven solutions.
• Stay up to date with emerging trends in AI, GenAI, and cloud-based ML technologies.

Qualifications

• 3+ years of experience in building and deploying AI/ML or GenAI solutions in production environments.
• Strong expertise in Azure Machine Learning, Azure Databricks, Microsoft Fabric, Azure AI Foundry, and Azure Cognitive Services.
• Proficiency in Python and major ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Hands-on experience with RAG architecture, prompt engineering, and LLM-based application development.
• Experience with MLOps/LLMOps pipelines, model tracking, and CI/CD using Azure DevOps.
• Familiarity with data integration across Microsoft Fabric, Azure Data Factory, or Synapse.
• Strong understanding of model lifecycle management, monitoring, and performance optimization using MLflow, App Insights, and Azure Monitor.
• Excellent problem-solving, debugging, and collaboration skills.

Good to Have

• Exposure to containerization and deployment tools (Docker, Kubernetes).
• Experience building APIs and model endpoints using FastAPI or Flask.
• Understanding of Data Engineering concepts, ETL workflows, and governance within Microsoft Fabric.
• Azure certifications such as Azure AI Engineer Associate or Azure Data Scientist Associate.
• Familiarity with Git, Terraform, or other Infrastructure-as-Code tools.

Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.