We are seeking an experienced Architect to lead the design and implementation of cutting-edge GenAI and Agentic AI solutions. This role involves leveraging advanced Databricks capabilities, including Genie and Agent Bricks, to build innovative use cases powered by Large Language Models (LLMs). You will be instrumental in shaping the future of AI within our organization, focusing on scalable and reliable data architectures.

This position offers an exciting opportunity to work with state-of-the-art AI technologies and contribute to high-impact projects. The ideal candidate will have a strong foundation in data engineering, LLM development, and enterprise-level AI solutions, driving efficiency and innovation.

Key responsibilities include architecting and deploying GenAI and Agentic AI solutions using Databricks Genie and Agent Bricks. You will develop LLM-powered use cases, construct robust data pipelines with Databricks, PySpark, and SQL, and implement Delta Lake, Unity Catalog, and medallion architecture.

Further duties involve optimizing Spark jobs for performance and cost, managing data ingestion and transformation, ensuring data quality, and developing enterprise ontologies and semantic data models. Preparing feature-ready datasets for AI/ML workloads and fine-tuning LLMs/ML models are also critical aspects of this role.

Proven experience in designing and implementing GenAI and Agentic AI solutions, including proficiency with Databricks Genie, Agent Bricks, and Mosaic AI. A strong understanding of LLM development, prompt engineering, RAG, and model evaluation is essential.

Expertise in building scalable data pipelines using Databricks, PySpark, and SQL, along with practical experience in Delta Lake, Unity Catalog, and medallion architecture. The ability to optimize Spark jobs and perform comprehensive data ingestion and transformation from diverse sources is required. Experience in developing enterprise ontologies, taxonomies, and semantic data models is also a key requirement.