AI Engineer

co.brick Talents; United States; Remote; USD 110,000 - 160,000; Full time

Job summary

co.brick talents is hiring a Data Engineer / AI Engineer for a fully remote, long-term project in the insurance domain. You will design robust data pipelines, implement OCR/IDP workflows, and deliver AI-driven automation within the Microsoft Azure ecosystem.

The role requires strong SQL skills, experience with Azure Databricks, Synapse, Data Lake, and familiarity with NLP and multilingual document processing. Collaboration with international stakeholders is essential.

Qualifications

• Data Engineer/AI Engineer with commercial experience.
• Hands-on with Azure Databricks, Azure Synapse Analytics, and Azure Data Lake.
• Experience with OCR/IDP or Azure AI Document Intelligence.
• Strong knowledge of NLP and multilingual document processing.
• SQL Server and BI stack (SSIS, SSRS, SSAS).
• Data Modeling, Data Warehousing, Data Mining, and DataOps.
• Exposure to ML projects and modern AI practices.
• Excellent English communication for international environment.

Responsibilities

• Design and develop scalable data processing solutions within the Azure ecosystem.
• Build and optimize ETL/ELT pipelines using Azure Databricks and Azure Synapse Analytics.
• Develop OCR-based solutions for automated document processing.
• Integrate extracted data with enterprise applications and reporting systems.
• Collaborate with business stakeholders to identify new automation opportunities.
• Participate in architecture discussions and contribute to DataOps best practices.
• Support the implementation of AI and Machine Learning initiatives.

Skills

Data Engineering

AI Engineering

Azure Databricks

Azure Synapse Analytics

Azure Data Lake

OCR/IDP

NLP

SQL Server

SSIS

SSRS

SSAS

Data Modeling

Data Warehousing

DataOps

ML

English Communication

Tools

Azure Databricks

Azure Synapse Analytics

Azure Data Lake

Job description

co.brick talents— powered by AI, powered by people.

Location: 100% Remote

Working Hours: Standard 9:00 – 17:00 (CET/CEST)

Contract Duration: 12+ months (long-term initiative)

Client Sector: International Insurance

On behalf of our client, a global leader in the insurance sector, we are looking for an experienced Data Engineer / AI Engineer to join a long-term initiative. In this role, you will focus on delivering intelligent document processing (IDP) and AI-driven automation solutions within the Microsoft Azure ecosystem.

About the Project & Client Initiatives

You will design and build robust data pipelines, OCR workflows, and AI solutions supporting key business processes, including:

OCR automation for cash register reports.

Intelligent data extraction from receipts and invoices.

Document data extraction and integration with downstream enterprise systems.

Digitization and automation of paper-based customer surveys and multilingual forms.

Combining OCR with text analytics and sentiment analysis.

Supporting new AI-driven automation initiatives emerging in the project pipeline.

Key Responsibilities

Design and develop scalable data processing solutions within the Azure ecosystem.

Build and optimize ETL/ELT pipelines using Azure Databricks and Azure Synapse Analytics.

Develop OCR-based solutions for automated document processing.

Integrate extracted data with enterprise applications and reporting systems.

Collaborate with business stakeholders to identify new automation opportunities.

Participate in architecture discussions and contribute to DataOps best practices.

Support the implementation of AI and Machine Learning initiatives.

Required Skills & Experience

Data Engineering Expertise: Proven commercial experience as a Data Engineer or AI Engineer.

Azure Cloud Ecosystem: Hands-on expertise with Azure Databricks, Azure Synapse Analytics, and Azure Data Lake.

Document Processing (IDP/OCR): Experience with OCR, Intelligent Document Processing, or Azure AI Document Intelligence.

AI & Text Analytics: Solid knowledge of Natural Language Processing (NLP), text analytics, and processing multilingual documents.

SQL & Microsoft Stack: Strong SQL skills, including SQL Server and the traditional BI stack (SSIS, SSRS, SSAS).

Data Fundamentals: Deep understanding of Data Modeling, Data Warehousing, Data Mining, and DataOps methodologies.

Modern AI Practices: Exposure to Machine Learning projects and familiarity with AI-assisted development tools.

Communication: Excellent English communication skills for working in an international environment.