AI Engineer: Data Pipelines, AI/ML & BI Automation

ITAC Solutions; Birmingham (AL); On-site; USD 130,000 - 150,000; Full time

Benefits offered by this job

End-to-end ownership

Direct collaboration with stakeholders

Microsoft Fabric exposure

Modernize legacy pipelines

High visibility across IT & business

Job summary

ITAC Solutions in Birmingham, AL is hiring an AI Engineer to own data integration, analytics and AI/ML development. You will feed enterprise data, build Power BI models, and prototype AI workflows with business stakeholders.

The role blends data engineering and AI/ML, requiring hands-on experience with Azure Data Factory, Power BI, and Python. Collaboration with stakeholders and readiness to handle ETL tasks are essential.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or related field.
• Hands-on experience with Azure Data Factory and/or Boomi.
• Experience building Power BI semantic models (not just surface-level dashboards).
• Track record taking AI/ML solutions from prototype to production.
• Comfortable splitting time between AI/ML work and ETL/data-plumbing work.
• Experience with Microsoft Fabric or agentic AI/workflow orchestration (preferred).

Responsibilities

• Build and maintain data integrations from ERP, EHS, and operational systems into Azure SQL.
• Develop and maintain Power BI semantic models and executive dashboards.
• Prototype and deploy AI/ML solutions (forecasting, anomaly detection, classification).
• Build agentic workflows to automate multi-step business processes.
• Partner directly with business users to define and test AI use cases.
• Modernize and clean up legacy data pipelines.
• Apply Python across data engineering, analytics, and AI/ML work.

Job description

ITAC Solutions in Birmingham, AL is hiring an AI Engineer to own data integration, analytics and AI/ML development. You will feed enterprise data, build Power BI models, and prototype AI workflows with business stakeholders.

The role blends data engineering and AI/ML, requiring hands-on experience with Azure Data Factory, Power BI, and Python. Collaboration with stakeholders and readiness to handle ETL tasks are essential.