- Design and implement GenAI 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, PySpark, 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
- Design and develop enterprise ontologies, taxonomies, vocabularies, and semantic data models.
- Support AI/ML workloads by preparing high-quality,
feature-ready datasets
- Develop and fine-tune LLMs/ML models using Databricks MLflow and Mosaic AI
- Implement prompt engineering, model evaluation, and guardrails for enterprise GenAI use cases
- Integrate AI solutions with enterprise data and business workflows
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.