Active Top-Secret clearance with capability to obtain SCI/CI Poly if needed.
Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or equivalent experience).
Minimum 10 years of relevant professional experience.
Responsibilities
Design and govern an enterprise-level parsing and document preprocessing architecture for autonomous agents and LLM applications.
Create an end-to-end framework for ingesting and validating multi-format unstructured data.
Build resilient, cost-optimized data pipelines for high-throughput AI environments.
Define unified semantic data schemas and advanced metadata tagging protocols.
Architect retrieval infrastructure with indexing strategies and secure access controls.
Collaborate with data governance and security teams to ensure compliance and data lineage.
Benefits
Company-subsidized medical premiums for employees and dependents.
Dental and vision coverage.
401k retirement savings plan with up to 4% match.
Health Savings Account (HSA), FSA, and DCFSA options.
Company-paid short/long-term disability and life insurance.
Generous paid time off and all 11 federal holidays.
Legal and identity protection services.
Bonuses for certifications and reimbursement.
Employee perks including UberOne and company outings.
Full Job Description
PID: 26-22-10-016
Summary
E-INFOSOL LLC is seeking a motivated and results-driven Parsing Architect to join our growing team in Chantilly, VA.
Key Responsibilities
Responsible for the systemic design, scaling strategy, and governance of an enterprise-level parsing and document preprocessing architecture engineered specifically for autonomous agents and LLM application stacks.
Design the end-to-end framework that governs how massive, multi-format unstructured data lakes are ingested, validated, and programmatically segmented before indexing. By evaluating and orchestrating cutting-edge parsing technologies-ranging from traditional layout engines and Optical Character Recognition (OCR) to multimodal vision-language models and specialized document processing APIs.
Build resilient, cost-optimized pipelines capable of streaming contextually rich data into high-throughput AI environments.
Operate across the boundaries of core data engineering and cognitive computing infrastructure and define unified semantic data schemas, chunking rules, and advanced metadata tagging protocols to maintain context across massive documentation libraries.
Architect the retrieval infrastructure, establishing the indexing strategies, vector database integrations, and high-assurance access controls necessary for highly secure and accurate hybrid search (GraphRAG).
Partner with data governance, security, and corporate compliance teams and enforce strict lineage tracing and automated PII/PHI filtering, ensuring that the enterprise data fed into evolving LLM context windows remains performant, compliant, and secure.
Required Qualifications
Active Top-Secret clearance with capability to obtain SCI/CI Poly if needed to meet contract requirements.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline (or equivalent experience).
Minimum 10 years of relevant professional experience.
Benefits
Medical - company subsidized premiums for employees, including family and dependent options.
