AI Solution Engineer

Experience : 2-5 Years Key Responsibilities Build and test extraction components Write and refine prompts and classification logic. Build parsers for different attachment formats, including PDFs, scanned documents, images, and email threads. Prepare and label unstructured documents for testing, and maintain evaluation datasets. Run accuracy tests, track results against confidence thresholds, and report findings to the team.

Help implement review-queue flags for low-confidence, missing-information, or mismatched items. Support integration work with email inboxes and workflow queues, and help troubleshoot issues during testing and deployment. Write clean, documented code and unit tests. Required Skills Good Python skills and understanding of core CS concepts (data structures, APIs, JSON, REST). Understanding of how LLMs work, and familiarity with prompt engineering through projects, internships, or coursework.

Basic knowledge of text extraction from PDFs and images. Understanding of classification and metrics such as accuracy, precision, and recall. Comfort with Git and the command line. Attention to detail, since small extraction errors can send a document to the wrong channel. Nice to Have Projects involving document processing, OCR, invoice or form extraction, or email automation (a GitHub link is a plus). Exposure to Azure, AWS, or GCP AI services.

Basic SQL and experience working with structured reference data. Interest in or exposure to the insurance or financial services domain. Degree in Computer Science, IT, Data Science, or a related field.