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# Data & AI Architect

- **Company:** Q1 Technologies, Inc.
- **Location:** Aurora, IL, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Continuous Delivery, Continuous Integration, Data as a Services, Data Architecture, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Azure Data Lake, SQL Databases, Feature Store, Feature Engineering, Azure Data Factory, Pytorch, Apache Spark, Containerization, Data Lakes, Scikit Learn, Kubernetes, Real-time Inference, Machine Learning Operations, Azure AI, Api Design, Azure Synapse Analytics, Software Version Control, Data Pipelines, Serverless Computing, Docker, Databricks
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-ai-architect-aurora-il--dac01ec0-0281-48bf-89a5-4922bb4cf2e6

## About the Role

Artificial Intelligence (AI), Machine Learning, Artificial Intelligence (AI), Data Lake, Microsoft Windows Azure, Equipment Maintenance/Repair, Continuous Deployment/Delivery, Continuous Integration, Application Programming Interface (API), Docker, Must Have Technical/Functional Skills
Strong expertise in Microsoft Azure AI & Data services: Azure Machine Learning, Azure Synapse, Azure Data Factory, Azure Data Lake, Azure Functions.
Hands-on experience with Databricks: Spark, Delta Lake, MLflow, notebooks, and job orchestration.
Proficiency in Python, SQL, and ML frameworks like TensorFlow, PyTorch, Scikit-learn.
Experience with MLOps tools and practices: CI/CD, model versioning, monitoring, and retraining.
Deep understanding of data architecture, feature stores, and real-time inference.
Familiarity with containerization (Docker, Kubernetes) and API development for model serving.
Excellent communication and stakeholder management skills.
Azure certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert) are a plus.

## Description

Architect end-to-end AI/ML solutions using Azure services (Azure ML, Synapse, Data Lake, etc.) and Databricks.
Lead technical design sessions and guide teams on best practices for scalable and secure AI solutions.
Collaborate with data scientists, engineers, and business stakeholders to translate business problems into AI solutions.
Design and implement MLOps pipelines for model training, deployment, monitoring, and governance.
Optimize data pipelines and feature engineering workflows using Spark and Delta Lake on Databricks.
Ensure compliance with data privacy, security, and governance standards.
Evaluate and integrate emerging AI technologies and frameworks.
Provide technical leadership and mentorship to junior architects and engineers.