Senior AI Engineer – Azure AI Foundry & Databricks

We are looking for a Senior AI Engineer with strong hands-on experience in Microsoft Azure AI Foundry, Generative AI, RAG, AI Agents, and Databricks. The ideal candidate will be responsible for designing, developing, deploying, and troubleshooting enterprise-grade AI solutions.
Key Responsibilities
Design and develop GenAI, RAG, and AI Agent solutions using Azure AI Foundry and Azure OpenAI.
Configure Foundry projects, models, Agents, tools, knowledge sources, memory, and integrations.
Implement and troubleshoot Agent tracing, backend tracing, observability, and monitoring.
Build RAG pipelines using Azure AI Search, vector, semantic, and hybrid search.
Implement AI evaluations, including groundedness, relevance, and response quality.
Design and configure AI guardrails and safety controls.
Work with Azure AI Document Intelligence and other Azure AI services.
Develop scalable AI backends and APIs using Python.
Build and troubleshoot AI/ML solutions using Azure Databricks.
Work with Databricks Agent Bricks, Genie, MLflow, and MLflow Tracing.
Manage AI/data governance using Databricks Unity Catalog, including permissions and attribute-based access control.
Troubleshoot production issues across Agents, RAG pipelines, Databricks jobs, models, and APIs.
Required Skills
7+ years of experience in AI/ML, GenAI, software engineering, or related areas.
Strong hands-on experience with Azure AI Foundry and Azure OpenAI.
Experience building AI Agents and RAG applications.
Strong knowledge of AI tracing, evaluation, groundedness, and guardrails.
Strong Python development and API integration experience.
Experience with Azure AI Search and Document Intelligence.
Hands-on experience with Azure Databricks, MLflow, and Unity Catalog.
Understanding of semantic, vector, and hybrid search.
Strong troubleshooting and problem-solving skills.
Good to Have
Experience with Databricks Agent Bricks and Genie.
Experience with Agent memory and enterprise AI governance.
Knowledge of LangChain, Semantic Kernel, Azure ML, or MLOps.
Experience with CI/CD and production AI deployments.

Work arrangement
No