Mission
Design, build, and optimize scalable data ingestion and document processing solutions that transform large volumes of unstructured insurance data into structured, AI-ready information. Enable downstream AI and retrieval systems by leveraging OCR, document intelligence, vector databases, and cloud-native data pipelines.
Responsibilities:
- Design and implement scalable data ingestion pipelines for processing high volumes of unstructured documents, including PDFs, scans, emails, and Office files.
- Integrate, configure, and optimize OCR and document extraction technologies to maximize text extraction accuracy and document understanding.
- Build automated workflows for document parsing, text cleaning, normalization, semantic chunking, and metadata enrichment.
- Develop connectors and integrations for document sources such as SharePoint, email systems, and enterprise repositories.
- Design and maintain vector database schemas and retrieval mechanisms to support Retrieval-Augmented Generation (RAG) solutions and AI applications.
- Ensure document processing pipelines meet enterprise security, compliance, performance, and availability requirements.
- Implement monitoring, validation, and quality-control mechanisms to identify and manage low-confidence OCR and extraction results.
- Optimize data processing workflows for scalability, reliability, and low-latency operations.
- Collaborate with AI Engineers, Backend Engineers, and Platform teams to deliver end-to-end AI-powered document processing solutions.
- Develop and maintain cloud-native data ingestion solutions on public cloud platforms.
Profile
Professional Experience
- 5-10 years of experience in Data Engineering, Data Processing, Document Intelligence, or related fields.
- Proven experience building scalable data ingestion and processing pipelines.
- Experience working with large volumes of unstructured and semi-structured data.
- Experience designing cloud-based data solutions.
Technical Skills
- Strong programming skills in Python.
- Strong SQL knowledge.
- Hands-on experience with AWS services, including:
- S3
- Step Functions
- CloudWatch
- Experience processing unstructured documents such as:
- PDF
- Word
- Excel
- PowerPoint
- Email content
- Experience building connectors and integrations with enterprise content repositories (e.g., SharePoint).
- Experience with OCR and document extraction tools (AWS Textract or equivalent).
- Experience designing and implementing data ingestion and transformation pipelines.
- Familiarity with vector databases and Retrieval-Augmented Generation (RAG) concepts.
- Experience with software development best practices:
- Git
- CI/CD
- Automated testing
Nice to Have
- Experience with Vector Databases.
- Experience with RAG architectures and AI/LLM-based applications.
- Experience with Azure cloud services.
- Experience with Databricks.
- Experience in Insurance, Banking, or other regulated industries.
Benefits
- Full access to foreign language learning platform
- Personalized access to tech learning platforms
- Tailored workshops and trainings to sustain your growth
- Medical insurance
- Meal tickets
- Monthly budget to allocate on flexible benefit platform
- Access to 7 Card services
- Wellbeing activities and gatherings