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AI Internal Tools Automation Engineer

James Yamamoto

Full-time · Job · Los_Angeles

About the role

We're building the operational backbone that lets our clinical research teams move faster without babysitting spreadsheets and manual handoffs. Fast-moving team, big problem: too many of our internal processes still run on tribal knowledge and copy-paste. You'll design and ship internal automation tools that connect our data systems, deployment pipelines, and research workflows into something coherent. Expect to touch everything from Airflow DAGs to internal APIs, with direct ownership over what ships. The tools you build will directly cut the hours our scientists spend on manual data wrangling, freeing them to focus on the science instead of the plumbing.

Responsibilities

  • Build and maintain internal automation pipelines connecting research and engineering systems
  • Own Airflow DAG design for recurring data and reporting jobs
  • Containerize internal tools with Docker and deploy them via Kubernetes
  • Partner directly with research scientists to identify manual bottlenecks worth automating
  • Monitor pipeline health and respond to failures before they block a team

Requirements

  • 3+ years building internal tooling or data automation systems
  • Hands-on experience with Airflow, Docker, and Kubernetes
  • Comfortable working directly with AWS-hosted infrastructure
  • Strong Python skills for scripting and pipeline logic
  • Ability to work independently with minimal process overhead

Benefits

  • Fully remote position
  • Competitive salary + equity
  • Health and dental insurance
  • Flexible working hours
  • Annual learning stipend

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Categories

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python airflow docker kubernetes aws

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python airflow docker kubernetes aws

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