Architect

Area(s) of responsibility

• 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