Data Integration Specialist ( AI Engineer )
Summary
An AI engineer on an enterprise Data & AI team who designs, builds, and deploys production-ready AI/ML and Generative AI solutions (RAG, prompt engineering) integrated with modern data platforms. Core stack includes Python/SQL, Azure, Microsoft Fabric, and Databricks with MLOps practices.
We are looking for an AI Engineer to join an enterprise Data & AI team and help build production-ready AI/ML and Generative AI solutions integrated with modern data platforms.
This is a great opportunity for someone who enjoys working across AI, Machine Learning, Data Engineering, and Cloud technologies and wants to work on enterprise-scale use cases.
What You'll Do
- Design, develop and deploy AI/ML solutions for enterprise data products
- Build Generative AI / LLM solutions, including RAG and prompt engineering
- Develop solutions for predictive analytics, anomaly detection and automation
- Integrate AI/ML capabilities into data pipelines and lakehouse platforms
- Build and manage model training, deployment, inference and monitoring workflows
- Work with Azure, Microsoft Fabric and/or Databricks environments
- Implement MLOps practices including model versioning, CI/CD, monitoring and retraining
- Partner with Data Engineers, Architects, Product Owners and business stakeholders
- Ensure AI solutions are scalable, reliable, explainable and production-ready
- Follow enterprise AI governance and Responsible AI practices
What We’re Looking For
- Strong Python and/or SQL skills
- Hands-on experience in Machine Learning / AI Engineering
- Experience with model development, evaluation and deployment
- Experience with Generative AI, LLMs, RAG and Prompt Engineering
- Experience with Databricks / MLflow / Model Registry is highly desirable
- Exposure to Microsoft Fabric and Lakehouse architectures is a plus
- Knowledge of data pipelines, feature engineering and orchestration
- Understanding of MLOps, CI/CD, Git and model monitoring
- Experience working in Agile enterprise environments
Nice to Have
- Data governance and data quality knowledge
- Experience integrating AI into enterprise workflows
We're looking for an engineer who can go beyond building models — someone who can take AI from experimentation to production and integrate it into real enterprise data products and business processes.