DevOps Engineer, Data & AI Platform

SimplePractice; Santa Monica (CA); On-site; USD 144,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

401(k) plan

Flexible time off

Mental health resources

Parental leave

Tuition reimbursement

ERGs

Job summary

SimplePractice in Santa Monica, CA, is seeking a DevOps Engineer to support and scale our Data and AI platform in production. You will build reliable infrastructure for data pipelines and ML systems, standardize deployment patterns, and ensure performance, observability, and cost efficiency across compute-intensive workloads.

The role requires 3+ years in DevOps/SRE, strong AWS experience, and hands-on Terraform, Docker, and Kubernetes expertise to drive CI/CD and model lifecycle automation.

Qualifications

• 3+ years of experience in DevOps, SRE, or infrastructure engineering.
• End-to-End MLOps/LLMOps Expertise: deploying and maintaining ML/AI workflows.
• Strong cloud experience (AWS preferred).
• Proficiency with Terraform (or similar IaC tools).
• Experience with Docker and Kubernetes.
• Familiarity with CI/CD and Git-based workflows.
• Experience supporting data platforms (e.g., Airflow, Kafka, Spark).
• Programming/scripting (Python, Bash).
• Experience with observability tools and practices.

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 Machine Learning 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

SRE

Cloud AWS

Terraform

Docker

Kubernetes

CI/CD

Git workflows

Data platforms

Python/Bash

Observability

Tools

Terraform

Docker

Kubernetes

Airflow

Kafka

Spark

Git

Job description

About Us

At SimplePractice, we are improving access to quality care by equipping health and wellness clinicians with all the tools they need to thrive in private practice.

More than 250,000 providers trust SimplePractice to build their business through our industry-leading software with powerful tools that simplify every part of practice management. From admin work to clinical care, our suite of innovative solutions work together to reduce administrative burden-empowering solo and small group practitioners to thrive alongside their clients.

Award-winning and people-first, SimplePractice is shaping the future of health tech. In 2026, we were recognized by BuiltIn as a Best Remote Company to Work For, Software Guru's Best Places to Code, Becker Healthcare Telehealth Companies to Know, and we won a MedTech Breakthrough Award for Best Practice Management Solution Provider.

The Role

We are hiring a DevOps Engineer to support and scale our Data and AI platform in production. This role focuses on building reliable infrastructure for data pipelines and ML systems, standardizing deployment patterns, and ensuring performance, observability, and cost efficiency across compute-intensive workloads.

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 Machine Learning 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

Desired Skills & Experience

• 3+ years of experience in DevOps, SRE, or infrastructure engineering
• End-to-End MLOps/LLMOps Expertise: Experience deploying and maintaining ML/AI workflows. Familiarity with the unique nature of promoting AI assets (models, datasets, and code) through the lifecycle.
• Strong cloud experience (AWS preferred)
• Proficiency with Terraform (or similar IaC tools)
• Experience with Docker and Kubernetes
• Familiarity with CI/CD and Git-based workflows
• Experience supporting data platforms (e.g., Airflow, Kafka, Spark, or similar)
• Programming/scripting (Python, Bash, or similar)
• Experience with observability tools and practices

Preferred Qualifications

• Experience with MLOps tooling (e.g., MLflow, SageMaker, Kubeflow)
• Familiarity with LLM-based systems and AI observability(token usage tracking, prompt versioning) and evaluation loops
• Experience with real-time or high-throughput data systems
• Exposure to security and compliance requirements (e.g., SOC 2, HIPAA)
• Experience with specific MLOps tooling (Outerbounds, SageMaker, Metaflow) and vector database

Benefits

We offer a competitive benefits program including:

• Medical, dental, vision, life & disability insurance
• 401(k) plan with company match
• Flexible Time Off (FTO), wellbeing days, paid holidays, and summer Fridays
• Mental health resources
• Paid parental leave & Backup Care
• Tuition reimbursement
• Employee Resource Groups (ERGs)

California Job Applicant Privacy Notice

Thank you for your interest in opportunities at SimplePractice LLC (\"SimplePractice\" or \"us\" or \"we\" or \"our\"). Please note that when you submit your resume or application materials to us for employment purposes, you are subject to the SimplePractice California Job Applicant Privacy Notice. For more information about our privacy practices, please contact us at .

Base salary is one component of total compensation. Employees may also be eligible for an annual bonus or commission. Some roles may also be eligible for overtime pay.

The amount below represents the expected annual base compensation range for this job requisition. Ultimately, in determining your pay, we'll consider many factors including, but not limited to, skills, experience, qualifications, geographic location, and other job-related factors.

Base Compensation Range$144,300—$180,350 USD