DevOps Engineer, Data & AI Platform | Remote Friendly

SimplePractice; Los Angeles (CA); On-site; MXN 1,124,000 - 1,406,000; Full time

Benefits offered by this job

Privatized Medical, Dental & Vision

Work From Home stipend

Annual Bonus

Tuition Reimbursement

Relocation bonus

Catered Lunch

Savings Funds

ERGs

Job summary

SimplePractice LLC is hiring a DevOps Engineer to scale our Data and AI platform in production. You will build reliable infrastructure for data pipelines and ML workloads, standardize deployment patterns, and ensure performance, observability, and cost efficiency in compute-intensive tasks.

The role emphasizes end-to-end ML/LLMOps, strong cloud experience (AWS), IaC with Terraform, and container orchestration using Docker and Kubernetes.

Qualifications

• 3+ years in DevOps, SRE, or infra engineering.
• End-to-End MLOps/LLMOps: deploying ML/AI workflows.
• Strong AWS cloud experience; Terraform proficiency.

Responsibilities

• Build and operate infrastructure for data pipelines and AI/ML workloads.
• Develop and maintain CI/CD for application and model lifecycle (build, train, deploy).
• Manage Infrastructure as Code (Terraform) across environments.
• Support containerized workloads and orchestration (Docker, Kubernetes).
• Partner with ML teams and engineering to productionize models.
• 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.
• Reduce operational overhead through automation and tooling.

Skills

DevOps experience

MLOps/LLMOps

AWS

Terraform

Docker

Kubernetes

CI/CD

Airflow

Kafka

Spark

Python

Bash

Observability

Job description

SimplePractice LLC is hiring a DevOps Engineer to scale our Data and AI platform in production. You will build reliable infrastructure for data pipelines and ML workloads, standardize deployment patterns, and ensure performance, observability, and cost efficiency in compute-intensive tasks.

The role emphasizes end-to-end ML/LLMOps, strong cloud experience (AWS), IaC with Terraform, and container orchestration using Docker and Kubernetes.