Parsing Engineer (AI) | Senior

Amatriot Group, LLC
Chantilly, VA, United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$112,000 - $196,000
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Metadata Parsing Markdown Azure Machine Learning Unstructured Data Retrieval-Augmented Generation Large Language Models Generative AI Software Library

Job description

The Senior Parsing Engineer (AI) builds, optimizes, and maintains text extraction and chunking pipelines that feed unstructured data into large language model (LLM) ecosystems, vector databases, and retrieval-augmented generation (RAG) frameworks. This role preserves document structure and semantic context while transforming complex, multiformat content into clean, Markdown-formatted text. Working with AI researchers, data engineers, and ML platform teams, the engineer improves embedding accuracy, retrieval precision, and context window utilization while minimizing downstream model hallucinations., Text Extraction and Document Processing

  • Build and maintain high-fidelity extraction workflows for PDFs, charts, presentations, and web documents.
  • Preserve semantic layout and structural metadata, including hierarchies, headers, and bulleted lists.
  • Transform raw, unstructured content into clean, Markdown-formatted text for downstream AI processing.

Chunking and Advanced Parsing

  • Implement parent-child document relationships and sliding-window chunking strategies.
  • Develop multimodal, vision-based table extraction using tools such as Docling or layout-aware open-source libraries.
  • Write specialized code to parse and extract data embedded within tables.

Metadata and Retrieval Support

  • Enrich text chunks with metadata tags, including source lineage, temporal data, and classification levels.
  • Prepare parsed content for LLM ecosystems, vector databases, and RAG frameworks.
  • Support high-precision hybrid search through context-preserving extraction and metadata enrichment.

Pipeline Evaluation and Optimization

  • Benchmark and tune parsing pipelines to improve retrieval accuracy and context window utilization.
  • Optimize extraction and chunking workflows to maximize embedding accuracy and minimize downstream model hallucinations.
  • Collaborate with AI researchers, data engineers, and ML platform teams to refine pipeline performance.

Requirements

  • Bachelor’s degree required., * Minimum of 8 years of experience.

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