Azure AI Engineer

The Azure AI Engineer will be responsible for designing, developing, and deploying intelligent solutions using Azure AI services, Azure AI Foundry, Copilot Studio, and OpenAI technologies, while working on advanced projects involving Large Language Models (LLMs), forecasting and time series modeling, and Lakehouse architectures to drive business transformation and automation., * Design and implement AI/ML solutions using Azure Machine Learning, Azure AI Foundry, OpenAI on Azure, and Copilot Studio to deliver intelligent business applications.

• Build and fine-tune LLM-based applications for internal and customer-facing use cases.

• Develop and maintain Python-based data pipelines and ML models.

• Implement forecasting and time series models for demand prediction, sales forecasting, and operational planning.

• Integrate AI capabilities into business applications using Power Platform, Copilot Studio, and Azure Cognitive Services.

• Create autonomous AI Agents that can execute tasks independently while allowing users to control, customize, and run them for specific business workflows.

• Implement MCP (Model Context Protocol) for managing context across AI systems and ensure interoperability with enterprise data sources.

• Design and integrate A2A (Agent-to-Agent) communication protocols to enable seamless collaboration between autonomous agents for complex workflows.

• Design and build Lakehouse architecture leveraging Microsoft Fabric and Delta Lake, implementing Medallion Architecture best practices (Bronze, Silver, Gold layers) and metadata-driven pipelines to ensure data quality, scalability, and unified analytics across structured and unstructured data sources.

• Ensure responsible AI practices, including model monitoring, fairness, and explainability.

• Stay current with advancements in AI/ML, LLMs, and Microsoft's AI ecosystem.

• Maintains reliable and consistent attendance, including being punctual, dependable, and flexible to potential schedule changes to meet the needs of the department and the organization.

• Executes each essential duty satisfactorily to perform job successfully.

• Follows all safety procedures required in work area, wears PPE as needed, attends all safety meetings, and reports safety issues regarding equipment or unsafe/hazardous conditions.

• Performs effectively as a team member, able to work well with others, open to receive and give feedback, and treats everyone with respect.

• Takes ownership of own work and behavior, accepts accountability for own actions, encourages solutions, and communicates status of work/projects.

• Follows all department quality standards/criteria. Raises concerns and issues to management.

• Understands department's key performance indicators (KPIs) and contributes to achieve these goals both individually and as a team.

• Other duties as needed or required.

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time., The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 5+ years of experience in AI/ML engineering or related roles.

• Strong proficiency in Python and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).

• Hands-on experience with Azure AI services, Azure Machine Learning, and OpenAI on Azure.

• Experience building solutions with Copilot Studio and Power Platform.

• Solid understanding of forecasting techniques (ARIMA, Prophet, LSTM, etc.) and time series analysis.

• Familiarity with LLMs, prompt engineering, and fine-tuning techniques.

• Knowledge of Lakehouse architecture and tools like Azure Synapse, Databricks, or Microsoft Fabric.

• Best Practices Knowledge of Medallion Architecture.

• Strong understanding of Devops and MLOps, version control, and CI/CD for ML.

• Working knowledge of MCP (Model Context Protocol) for managing context across AI systems and enabling interoperability.

• Experience with A2A (Agent-to-Agent) communication protocols for orchestrating autonomous AI agents and multi-agent workflows.

• Excellent communication and collaboration skills.

PREFERRED QUALIFICATIONS

• Master's Degree in related field preferred

• Azure AI Engineer Certification Preferred

• Microsoft Fabric Certification Preferred