Job Title

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- 5–8 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.