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Software Development Engineer
Job in
Peoria, Peoria County, Illinois, 61639, USA
Listed on 2026-05-31
Listing for:
SPECTRAFORCE
Part Time
position Listed on 2026-05-31
Job specializations:
-
Software Development
AI Engineer
Job Description & How to Apply Below
Location:
Lake County, IL (Hybrid – 3 days/week onsite) Duration: 5+ months (possibility of extension)
Job Description:
We are looking for a Software Development Engineer to build and scale an AI-powered document parsing platform that extracts structured data from complex PDFs (pharmaceutical batch records, certificates, regulatory documents) using OCR, LLMs, and RAG. You will work across the full stack — backend AI pipelines, frontend chat interface, and cloud infrastructure.
- Design and develop production-grade RAG (Retrieval-Augmented Generation) pipelines for domain-specific document querying with hybrid search, reranking, and multi-agent answer synthesis
- Build and optimize document processing pipelines using AWS Textract for OCR extraction from tables, handwritten content, and structured forms
- Integrate and orchestrate multiple LLM models (Claude, Gemini) for intent classification, data extraction, validation, and conversational AI
- Develop and maintain the FastAPI backend — REST APIs, streaming endpoints (SSE), authentication, and background task processing
- Build responsive frontend features using Next.js, React, and Type Script — chat interface, PDF viewer with highlights, real-time progress tracking
- Manage cloud infrastructure on AWS — EC2 deployment, S3 storage, RDS (Postgre
SQL), and IAM configuration - Work with vector databases (Weaviate) and graph databases (Neo4j) for semantic search and structural document querying
- Implement chunking strategies, embedding generation, cross-encoder reranking, and semantic caching for accurate document retrieval
- Deploy and monitor AI models and services in production — model fallback chains, retry mechanisms, error handling
- Write clean, maintainable code with proper logging, error handling, and documentation
- RAG systems — vector search, embeddings, chunking, reranking (production-grade)
- LLM integration — prompt engineering, structured output, multi-model orchestration
- REST API design with streaming (SSE)
- Weaviate, Neo4j, or similar vector/graph databases
- Gemini Vision or GPT-4V for document image analysis
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