AI Platform Engineer - Atlanta, GA - FTE

We are seeking an AI Platform Engineer to help design, build, and scale an enterprise AI platform that enables secure, governed machine learning and generative AI capabilities across the organization.

In this role, you will partner with data science, product, cloud, and security teams to design, deploy, and optimize AI workloads while owning platform capabilities end-to-end. The position blends software engineering, cloud architecture, data engineering, and applied machine learning, helping teams build and operate AI solutions using technologies such as AWS, Databricks, Spark, and Python.

• Build and maintain large-scale Spark pipelines for data preparation, feature engineering, and model inference.
• Develop production-grade applications using Python, SQL, and modern software engineering practices.
• Design and build REST APIs and backend services supporting AI and machine learning workloads.
• Create shared frameworks, tools, and platform components to standardize and accelerate AI development.
• Deploy and operationalize machine learning models in partnership with data science teams.
• Implement secure and scalable cloud architectures on AWS, including services such as S3, Lambda, and IAM.
• Improve platform reliability, observability, and performance across AI workloads.
• Apply security best practices, including IAM design, data protection, and secrets management.
• Contribute to CI/CD pipelines and infrastructure-as-code using tools such as Terraform.
• Support GenAI initiatives, including prompt engineering and retrieval-augmented generation (RAG).
• Monitor production systems, troubleshoot issues, and optimize cost and performance.

• Experience building large-scale data pipelines with Spark or PySpark.
• Strong programming experience in Python and SQL.
• Experience designing and integrating REST APIs and backend services.
• Hands‑on experience with AWS services such as S3, Lambda, and IAM.
• Experience supporting the machine learning lifecycle, including model training, deployment, and monitoring.
• Strong understanding of software engineering best practices, including CI/CD, testing, and version control.
• Experience with Databricks, including tools such as Delta Lake or MLflow.
• Familiarity with GenAI technologies, including prompt engineering or RAG patterns.
• Experience with Terraform or infrastructure-as-code tools is a plus.