W2 ONLY - NO CORP'S - NO VISA TRANSFER- NO 3RD PARTY PASS THROUGHS Primary Job Responsibilities • Design, develop, and implement complex data pipelines for AI/ML, including those supporting RAG architectures, using technologies such as Python, Snowflake, AWS, GCP, and Vertex AI. • Implement on end-to-end generative AI pipelines, from data ingestion to pipeline deployment and monitoring. • Build and maintain data pipelines that ingest, transform, and load data from various sources (structured, unstructured, and semi-structured) into data warehouses, data lakes, vector databases (e.g., Pinecone, Weaviate, Faiss - consider specifying which ones you use or are exploring), and graph databases (e.g., Neo4j, Amazon Neptune - same consideration as above). • Develop and implement data quality checks, validation processes, and monitoring solutions to ensure data accuracy, consistency, and reliability. • Implement end-to-end generative AI data pipelines, from data ingestion to pipeline deployment and monitoring. • Develop complex AI systems, adhering to best practices in software engineering and AI development. • Work with cross-functional teams to integrate AI solutions into existing products and services. • Keep up-to-date with AI advancements and apply new technologies and methodologies to our systems. • Assist in mentoring junior AI/data engineers in AI development best practices. • Implement and optimize RAG architectures and pipelines. • Develop solutions for handling unstructured data in AI pipelines. • Implement agentic workflows for autonomous AI systems. • Develop graph database solutions for complex data relationships in AI systems. • Integrate AI pipelines with Snowflake data warehouse for efficient data processing and storage. • Apply GenAI solutions to insurance-specific use cases and challenges.