AI Solution Engineer
Posted
Description
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.