> Markdown version of [/jobs/ext/3190920-data-ai-architect](https://www.wearedevelopers.com/jobs/ext/3190920-data-ai-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data & AI Architect

- **Company:** Apptad Inc.
- **Location:** Atlanta, GA, United States
- **Salary:** $122,600.0 - $204,400.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Continuous Integration, Data as a Services, Data Architecture, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Azure Data Lake, SQL Databases, Feature Engineering, Azure Data Factory, Pytorch, Apache Spark, Containerization, Data Lakes, Scikit Learn, Kubernetes, Machine Learning Operations, Api Design, Azure Synapse Analytics, Software Version Control, Data Pipelines, Serverless Computing, Docker, Databricks
- **Published:** September 10, 2026
- **Apply:** https://www.careerjet.com/jobad/us961d74491bbaf284ce04c346351774e5

## About the Role

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.

## Description

Azure certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert) are a plus.
Roles & Responsibilities
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.


## Related Videos

- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud)
- [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source)

## Related Articles

- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)