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# Data Engineer Document AI Engineer Remote need USC

- **Company:** INNOVATIVE TECH SOLUTIONS INC
- **Location:** Washington, DC, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Google Docs, Python (Programming Language), Machine Learning, SQL Databases, Unstructured Data, Apache Spark, Reliability of Systems, Document Classification, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.wayup.com/i-j-Data-Engineer-Document-AI-Engineer-Remote-need-USC-INNOVATIVE-TECH-SOLUTIONS-INC-134289755142649/

## About the Role

Must be a U.S. Citizen (USC) - required for this engagement
Available for Corp-to-Corp (C2C) contracting arrangement
Proven experience as a Data Engineer with strong proficiency in Python, SQL, and Spark
Hands-on experience with Document AI tools such as Google Document AI, AWS Textract, or Azure Form Recognizer
Experience with cloud platforms (GCP, AWS, or Azure) and data warehousing solutions
Familiarity with NLP frameworks, OCR technologies, and unstructured data processing
Strong understanding of data modeling, pipeline orchestration (Airflow, etc.), and CI/CD practices
Excellent problem-solving skills and ability to work independently in a remote environment

## Description

Innovative Tech Solutions Inc is looking for a talented Data Engineer / Document AI Engineer to join our growing remote team. This is an exciting Corp-to-Corp (C2C) opportunity for a driven technologist ready to shape the future of intelligent document processing and data pipelines. If you're passionate about AI-driven data solutions and want to make a real impact, we want to hear from you!
Responsibilities:
Design, build, and maintain scalable data pipelines and ETL/ELT workflows
Develop and deploy Document AI solutions for intelligent document processing and extraction
Implement and optimize machine learning models for document classification, OCR, and NLP tasks
Collaborate with data scientists and business stakeholders to translate requirements into technical solutions
Manage and integrate structured and unstructured data across cloud and on-premise environments
Monitor data quality, pipeline performance, and system reliability
Contribute to the architecture and continuous improvement of the data platform infrastructure


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