Responsibilities

Develop end‑to‑end AI/ML solutions using Azure Machine Learning, Azure AI Foundry, OpenAI on Azure, and Copilot Studio.
Build and fine‑tune LLM‑based applications for both internal and customer‑facing use cases.
Create and maintain Python‑based data pipelines and ML models.
Implement forecasting and time‑series models for operational and business planning.
Integrate AI capabilities into business applications using the Power Platform, Azure Cognitive Services, and Copilot Studio.
Develop autonomous AI Agents and enable A2A (Agent‑to‑Agent) communication for complex workflow orchestration.
Implement MCP (Model Context Protocol) to support context sharing and system interoperability.
Architect and build Lakehouse solutions using Microsoft Fabric and Delta Lake following Medallion Architecture best practices.
Ensure Responsible AI: model monitoring, fairness, and explainability.
Stay current on new AI/ML, LLM, and Microsoft ecosystem innovations.
Collaborate effectively across teams, uphold quality standards, and support department KPIs.
Other duties as assigned; some travel may be required.

Basic qualifications

5+ years in AI/ML engineering or similar roles.
Strong Python skills and experience with ML frameworks (scikit‑learn, PyTorch, TensorFlow).
Hands‑on experience with Azure AI services, Azure ML, and OpenAI on Azure.
Experience building solutions with Copilot Studio and Power Platform.
Strong forecasting/time‑series modeling skills (ARIMA, Prophet, LSTM, etc.).
Knowledge of LLMs, prompt engineering, and fine‑tuning.
Experience with Lakehouse architectures (Azure Synapse, Databricks, Microsoft Fabric).
Familiarity with Medallion Architecture best practices.
Strong DevOps/MLOps foundation with CI/CD for ML.
Experience with MCP and A2A communication for autonomous agents.
Excellent communication and collaboration skills.

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