Job Description
Key Responsibilities
- Design and implement Gen AI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, Mosaic AI (model training, evaluation, prompt engineering, RAG)
- Experience Build LLM-powered use cases
- Design and build scalable data pipelines using Databricks, Py Spark, and SQL
- Implement Delta Lake, Unity Catalog, and medallion architecture
- Optimize Spark jobs for performance, cost, and scalability
- Perform data ingestion, transformation, and enrichment from multiple sources
- Ensure data quality, reliability, and observability across pipelines
- Support AI/ML workloads by preparing high‑quality, feature‑ready datasets
- Develop and fine-tune LLMs/ML models using Databricks ML flow and Mosaic AI
- Implement prompt engineering, model evaluation, and guardrails for enterprise Gen AI use cases
- Integrate AI solutions with enterprise data and business workflows
- Design and implement Gen AI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, Mosaic AI (model training, evaluation, prompt engineering, RAG)
- Experience Build LLM-powered use cases
- Design and build scalable data pipelines using Databricks, Py Spark, and SQL
- Implement Delta Lake, Unity Catalog, and medallion architecture
- Optimize Spark jobs for performance, cost, and scalability
- Perform data ingestion, transformation, and enrichment from multiple sources
- Ensure data quality, reliability, and observability across pipelines
- Support AI/ML workloads by preparing high‑quality, feature‑ready datasets
- Develop and fine-tune LLMs/ML models using Databricks ML flow and Mosaic AI
- Implement prompt engineering, model evaluation, and guardrails for enterprise Gen AI use cases
- Integrate AI solutions with enterprise data and business workflows