About the Role :

We are seeking a highly skilled AI Developer with deep expertise in integrating locally trained AI/ML models into enterprise-grade production systems. The ideal candidate must have strong experience with Azure cloud infrastructure, hands-on knowledge of the Model Context Protocol (MCP), proven experience leveraging AI Foundry, and in-depth expertise in Generative AI (GenAI) for building and deploying enterprise-ready solutions.

Key Responsibilities :

- Integrate and optimize locally trained AI/ML and Generative AI models within enterprise applications.

- Architect, build, and maintain scalable AI solutions using Azure services (Azure ML, Azure Kubernetes Service, Azure Functions, etc.).

- Implement and manage AI integration workflows leveraging the Model Context Protocol (MCP).

- Use AI Foundry to design, orchestrate, and operationalize AI workflows across multiple environments.

- Develop and integrate Generative AI solutions (LLMs, RAG, embeddings, fine-tuning) into production systems.

- Collaborate with cross-functional teams to design and implement AI-driven features in enterprise applications.

- Ensure enterprise-grade scalability, security, and performance in deployed AI systems.

- Work with Azure DevOps for CI/CD pipelines, monitoring, and lifecycle management of AI solutions.

- Provide technical expertise on AI model deployment, retraining workflows, and integration with enterprise applications.

Required Skills & Experience :

- Proven experience as an AI Developer / AI Engineer in enterprise environments.

- Strong hands-on experience with Azure AI/ML ecosystem (Azure Machine Learning, Azure Databricks, Cognitive Services, Azure Synapse, etc.).

- In-depth expertise in Generative AI (GenAI) including LLMs, RAG, embeddings, fine-tuning, and custom deployments.

- Hands-on expertise with Model Context Protocol (MCP) for connecting and orchestrating AI systems.

- Experience using AI Foundry to standardize and manage AI solutions at scale.

- Deep understanding of model deployment & integration (ONNX, APIs, containers, microservices).

- Proficiency in Python (preferred) and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

- Experience with MLOps practices (CI/CD, monitoring, retraining, governance).

Nice to Have :

- Knowledge of data pipelines using Azure Data Factory, Synapse, or Databricks.

- Experience in enterprise security compliance and scalable multi-tenant architectures.