Responsible for implementing AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions - includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready
Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices for insurance-specific data use cases and challenges
Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc.
Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems
Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment
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3-5+ years of experience across data engineering utilizing data solutions, SQL and NoSQL, Snowflake, ELT/ETL tools, CICD, Bigdata, GCP, Python/Spark, Datamesh, Datalake, Data Fabric
1+ year of hands-on experience supporting Gen AI initiatives in a data environment, ideally from insurance background
Experience implementing RAG (Retrieval-Augmented Generation) pipelines
Vector/graph database experience to structure data for large models using AI tools (steps include extraction, chunking, embedding, and ground strategies)
Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.