DevOps Engineer – Data & AI Platform

About the role

SimplePractice is looking for a DevOps Engineer to design, build, and operate the infrastructure that powers its Data and AI platform. You will work closely with machine‑learning and engineering teams to deliver reliable, scalable, and cost‑effective pipelines and model‑deployment workflows.

Key responsibilities

• Build and maintain infrastructure for data pipelines and AI/ML workloads on AWS.
• Develop and manage CI/CD pipelines for application and model lifecycles (build, train, deploy).
• Implement Infrastructure as Code using Terraform across multiple environments.
• Support containerized workloads with Docker and orchestrate them using Kubernetes.
• Collaborate with ML teams to productionize models and ensure observability, logging, and tracing.
• Improve reliability, scalability, and cost efficiency of data systems.
• Enforce security and access controls and automate operational tasks.

Required profile

• 3+ years of experience in DevOps, SRE, or infrastructure engineering.
• Hands‑on experience with end‑to‑end MLOps/LLMOps workflows.
• Strong cloud background, preferably AWS.
• Proficiency with Terraform (or similar IaC tools).
• Experience with Docker, Kubernetes, CI/CD, and Git‑based workflows.
• Familiarity with data platform technologies such as Airflow, Kafka, or Spark.
• Programming/scripting skills in Python or Bash.

Required skills

• AWS
• Terraform
• Docker
• Kubernetes
• CI/CD pipelines
• Git
• Python
• Bash
• Airflow
• Kafka
• Spark
• Observability tools (monitoring, logging, tracing)
• MLOps tools (MLflow, SageMaker, Kubeflow)
• Security and compliance frameworks (SOC 2, HIPAA)

What we offer

• Competitive benefits including medical, dental, vision, and vision coverage.
• Work‑from‑home stipend, flexible time off, paid holidays, and Summer Fridays.
• Monthly meal reimbursement, holiday bonus, and 15‑day Aguinaldo.
• Hybrid work schedule with catered lunch and relocation bonus.
• Employee Resource Groups and a supportive culture.