This role focuses on designing and implementing advanced Generative AI and Agentic AI solutions. You will leverage cutting-edge platforms like Databricks Genie and Mosaic AI to build and optimize LLM-powered applications.

The position requires expertise in creating scalable data pipelines and ensuring data quality within enterprise environments. We seek individuals adept at semantic data modeling and supporting AI/ML workloads with high-quality datasets.

Architect and deploy GenAI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, and Mosaic AI. Build LLM-powered use cases from concept to production.

Develop robust, scalable data pipelines with Databricks, PySpark, and SQL. Implement Delta Lake, Unity Catalog, and Medallion Architecture. Optimize Spark jobs for peak performance and cost-efficiency.

Prepare feature-ready datasets for AI/ML workloads. Design enterprise ontologies, taxonomies, and semantic data models. Fine-tune LLMs/ML models using Databricks MLflow and Mosaic AI, incorporating prompt engineering, model evaluation, and guardrails for secure GenAI deployment.

Proven experience in designing and implementing GenAI and Agentic AI solutions, including work with Databricks Genie, Databricks Agent Bricks, and Mosaic AI for model training, evaluation, and prompt engineering.

Expertise in building LLM-powered use cases and developing scalable data pipelines using Databricks, PySpark, and SQL. Familiarity with Delta Lake, Unity Catalog, and Medallion Architecture is essential.

Strong skills in optimizing Spark jobs for performance and cost, data ingestion, transformation, and enrichment. Experience in designing enterprise ontologies, taxonomies, and semantic data models is a plus. Ability to support AI/ML workloads by preparing high-quality datasets and fine-tuning LLMs/ML models using MLflow.