Senior Technical Lead (159406)

Design and implement RAG-based GenAI architectures on Databricks (ingestion, chunking, embeddings, vector search, retrieval). • Build and optimize LLM pipelines using Databricks (Workflows, MLflow, Unity Catalog, Model Serving). • Develop prompt engineering patterns, reusable prompt templates, and evaluation frameworks for LLM quality. • Integrate enterprise data sources into GenAI solutions while ensuring governance, lineage, and security via Unity Catalog. • Implement LLMOps practices: experiment tracking, model/version management, monitoring, and rollback strategies. • Collaborate with data engineers, MLOps engineers, and product teams to translate business problems into GenAI solutions. • Define and enforce coding standards, best practices, and design patterns for Databricks-based GenAI solutions. • Partner with security and compliance teams to ensure responsible AI use, data privacy, and adherence to internal policies. • Monitor and optimize cost, performance, and latency of LLM workloads on Databricks and AZURE cloud services., Develop new agents