Content Pipeline Engineer

NIH-NCBIBethesda, MD

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Overview

Schedule

Full-time

Career level

Senior-level

Remote

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Job Description

Overview

We are seeking a Content Pipeline Engineer to design and implement reusable pipelines for extracting, structuring, indexing, and retrieving information from permitting documents, maps, and other unstructured content.

The Content Pipeline Engineer will build document-processing capabilities spanning OCR, document parsing, multimodal extraction, metadata enrichment, vector indexing, semantic retrieval, and agentic workflows. The role will support documents such as PDFs, scanned forms, well files, plats, survey drawings, maps, and legal descriptions and make their content available to downstream applications and AI services.

This position is remote.

Duties & Responsibilities

Design and implement reusable ingestion and processing pipelines for PDFs, scanned documents, images, forms, maps, and other unstructured content.
Implement OCR and multimodal document-processing workflows for both standard documents and map-related materials.
Extract text, tables, metadata, identifiers, and domain-specific attributes from source documents.
Support extraction of information from plats and survey drawings, including legal descriptions, labels, bearings, distances, and other spatially relevant information.
Develop document parsing, classification, normalization, chunking, and metadata-enrichment processes.
Maintain linkage and provenance between extracted information, source documents, originating systems, and related business records.
Build document and vector indexes using OpenSearch or comparable technologies.
Implement embeddings, semantic search, and retrieval pipelines.
Develop APIs and reusable interfaces enabling downstream applications and AI services to search and retrieve document content.
Implement agentic workflows for activities such as document classification, extraction strategy selection, validation, exception handling, and quality assurance.
Establish confidence thresholds and human-review processes for uncertain or ambiguous extractions.
Work with GIS engineers to connect map and document extraction results with georeferenced and vectorized geometry.
Work with Data Scientists to create evaluation datasets and measure OCR, extraction, retrieval, and classification quality.
Build automated testing, monitoring, and observability for document-processing pipelines.
Optimize processing for accuracy, throughput, repeatability, and cost.

Educational Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field.

Requirements

5+ years of software engineering, data engineering, search, document-processing, or related experience.
Strong Python development experience and experience building production-grade data or content-processing pipelines.
Hands-on experience processing PDFs, images, scanned documents, and semi-structured content using OCR and document-extraction technologies.
Experience with document stores, search engines, or vector databases, including embeddings and semantic retrieval.
Experience with document parsing, classification, chunking, metadata enrichment, and preservation of source provenance.
Experience with LLM-enabled or agentic document-processing workflows, including extraction, validation, routing, or exception handling.
Experience building robust pipelines with automated testing, logging, monitoring, error handling, and quality controls.
Experience evaluating OCR and extraction quality using measurable criteria and confidence thresholds.
Strong problem-solving skills for working with complex and inconsistent document formats.

Bonus Skills

Experience with OpenSearch.
Experience with AWS document-processing, AI, or machine-learning services.
Experience with agentic frameworks such as LangChain, LangGraph, or similar orchestration frameworks.
Experience with multimodal models, vision-language models, or LLM-based document extraction.
Experience building RAG or enterprise semantic-search solutions.
Experience with maps, engineering drawings, plats, survey documents, or legal descriptions.
Experience extracting bearings, distances, coordinates, or other geospatial information from documents.
Experience working in the U.S. Federal Government space.

Experience with permitting, environmental, energy, land-management, or regulatory documents.

Benefits and Salary

We attract the best people in the business with our competitive benefits package that includes medical, dental and vision coverage, 401k plan with employer contribution, paid holidays, vacation, and tuition reimbursement.

If you enjoy being a part of a high performing, professional service and technology focused organization, please apply today!

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FAQs About Content Pipeline Engineer Jobs at NIH-NCBI

What is the work location for this position at NIH-NCBI?

This job at NIH-NCBI is located in Bethesda, MD, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.

What pay range can candidates expect for this role at NIH-NCBI?

Employer has not shared pay details for this role.

What employment applies to this position at NIH-NCBI?

NIH-NCBI lists this role as a Full-time position.

What experience level is required for this role at NIH-NCBI?

NIH-NCBI is looking for a candidate with "Senior-level" experience level.

Does NIH-NCBI allow remote work for this role?

Yes, this position at NIH-NCBI supports remote work, giving candidates the flexibility to work outside the primary office location.

What benefits are offered by NIH-NCBI for this role?

NIH-NCBI offers following benefits: Health Insurance, Dental Insurance, Vision Insurance, Paid Holidays, Paid Vacation, 401k Matching/Retirement Savings, and Tuition/Education Assistance for this position. Actual benefits may vary depending on the employer's policies and employment terms.

What is the process to apply for this position at NIH-NCBI?

You can apply for this role at NIH-NCBI either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.