Software Engineer
Description
GlobalLogic is working on an advisory engagement to design an AI-powered search assistant for project documentation accumulated over roughly 20 years, currently stored on an isolated, internet-disconnected file server. The dataset spans 2-3 TB including test artifacts, with core documents in the 1-10 GB range and about half the volume in the legacy .xls format. The goal is to let developers and SMEs query specification documents in natural language and get answers assembled across multiple related customization projects, instead of manually tracing code history and cross-referencing documents by hand. The target architecture connects the document store (likely SharePoint) to a generative AI search layer, with NotebookLM as the initial reference point and enterprise alternatives such as Vertex AI Agent Builder under evaluation.
Requirements
- 3+ years of commercial experience with Python, including work on data processing and ETL pipelines
- Experience parsing and transforming document formats (Excel including legacy .xls, PowerPoint, Word, PDF) using libraries such as pandas, openpyxl, xlrd, python-docx, python-pptx
- Experience with OCR technologies for extracting text from images and embedded objects (e.g. Tesseract, Google Vision API, Azure Computer Vision)
- Understanding of RAG (Retrieval-Augmented Generation) architectures, embeddings, and vector search
- Experience integrating with cloud storage and collaboration platforms via API (SharePoint / Microsoft Graph API or similar)
- Written and spoken English proficiency equivalent of B2 or higher
- Ability to work with incomplete requirements during an advisory and PoC phase
- Self-reliant, comfortable proposing and testing technical solutions with limited direction
Nice to have:
- Familiarity with NotebookLM, LangChain, LlamaIndex, or Vertex AI Agent Builder
- Experience designing incremental indexing or delta-update mechanisms for search systems
Experience working with enterprise clients in isolated or air-gapped network environments