Key Responsibilities
Provide technical leadership across AI architecture, model integration, and delivery.
Architect end-to-end AI pipelines using Databricks (Delta, Unity Catalog, MLflow, Model Serving).
Integrate GenAI platforms (Mosaic AI, Genie, Azure OpenAI) and orchestrate them via an MCP server for NL SQL and conversational intelligence.
Implement governed, cost-optimized MLOps pipelines with retraining, lineage, and observability.
Build multi-agent architectures combining text, tabular, and image models.
Enforce role-based security and governance through Unity Catalog.
Collaborate with UI (React) teams to integrate model outputs in Databricks web apps.
Lead feedback-driven model improvements and cross-functional mentoring.

Core Skills
Databricks Platform: SQL Warehouse, Unity Catalog, MLflow, Model Serving, OCR.
GenAI Tools: Mosaic AI, Genie, Azure OpenAI, LangChain, Vector Search, MCP Server for orchestrating AI tools and context.
ML Techniques: Isolation Forest, PSI/KSI drift detection, model retraining.
Vision Models: ViT, Grad-CAM, explainability methods.
Data Engineering: Spark, Python, Delta Lake, REST APIs.
Governance & Security: RBAC, lineage, masking, compliance policies.
Soft Skills: Architecture design, stakeholder alignment, communication.