DevOps Engineer – Data & AI Platform

About the role

SimplePractice is looking for a DevOps Engineer to design, build, and maintain the infrastructure that powers its Data and AI platform. You will work closely with machine‑learning and engineering teams to bring data pipelines and ML models into production, ensuring they are reliable, scalable, and cost‑effective.

Key responsibilities

• Build and operate infrastructure for data pipelines and AI/ML workloads.
• Develop and maintain CI/CD pipelines for application and model lifecycles (build, train, deploy).
• Manage Infrastructure as Code using Terraform across multiple environments.
• Support containerized workloads with Docker and Kubernetes orchestration.
• Implement monitoring, logging, and tracing for data flow and model performance.
• Improve reliability, scalability, and cost efficiency of data systems.
• Enforce security and access controls for data and infrastructure.
• Automate operational tasks to reduce manual overhead.

Required profile

• 3+ years of experience in DevOps, SRE, or infrastructure engineering.
• Hands‑on experience with end‑to‑end MLOps/LLMOps workflows.
• Strong background in cloud environments, preferably AWS.
• Proficiency with Terraform (or comparable IaC tools).
• Experience supporting data platforms such as Airflow, Kafka, or Spark.

Required skills

• AWS
• Terraform
• Docker
• Kubernetes
• CI/CD pipelines
• Git
• Python
• Bash
• Airflow
• Kafka
• Spark
• MLflow
• SageMaker
• Kubeflow

What we offer

• Competitive benefits package
• Opportunity to work on cutting‑edge AI and data infrastructure
• Collaborative, remote‑friendly culture with a distributed team