Save application

juullabs

Sep 15

Enterprise AI Systems Engineer

Onsite · Austin, Texas, United States; Dallas, Texas, United States; San Francisco, California, United States; Washington, District of Columbia, United States Austin, Texas, United States; Dallas, Texas, United States; San Francisco, California, United States; Washington, District of Columbia, United States

phoenixpythonjavascripttypescriptawsgcp global information technology

greenhouse

Match & cover letter

Create a profile to see your match and get a cover letter for this role.

Create profile and match

Source: greenhouse Verified source

Never pay or share passwords or codes with an employer. How to spot a fake job

AI TL;DR

You will manage AI platforms and ensure their effective use across the company. This role involves hands-on engineering and administration of enterprise AI systems.

AI match

Clear role · 80/100 against the market band on this page.

Interview prep for this job

  1. What would you ship in the first month as Enterprise AI Systems Engineer at juullabs?
  2. Which tradeoff in the description would you ask about first?
  3. How do you explain a production incident to this team?
  4. What would you measure in the first two weeks?
  5. Which part of your last project maps to this stack?

Five questions are free. The rest are Pro. See Pro

Similar roles

  • No similar roles on the board yet.

Job description

You will manage AI platforms and ensure their effective use across the company. This role involves hands-on engineering and administration of enterprise AI systems.

Details

  • Austin, Dallas, San Francisco, Washington, work from office
  • $126,000—$206,000 USD based on location
  • 5+ years in software, cloud, or platform engineering
  • Skills: Python, JavaScript, TypeScript, AWS, GCP

The work

  • Administer enterprise AI platforms and manage user provisioning and security settings
  • Build and maintain useful content for AI platforms, driving adoption among users
  • Monitor platform availability and handle user issues and escalations
  • Architect and run AI workloads on AWS and GCP, ensuring security and performance