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AI Idle Resource Termination Automation Developer

Max Dubois

Full-time · Job · New_York

About the role

Engineers spin up cloud resources and forget about them. A dev database running 24/7 for a project that ended 6 months ago. A GPU instance nobody connected to since the experiment completed. An S3 bucket with test data from a feature that got cancelled. These forgotten resources collectively waste $4-8M per year across our enterprise clients. Our idle resource termination system identifies unused resources through behavioral signals — zero connections, no read/write activity, missing from infrastructure-as-code, not associated with any active project — and safely terminates them after confirming with the resource owner. "Safely" means: notifying before terminating, preserving snapshots for recovery, and never touching resources that are legitimately idle by design. As a junior developer, you'll build the resource behavioral analysis module: querying cloud provider APIs for utilization metrics, applying idle classification rules, and generating the candidate lists that feed the human-review and auto-termination workflows. Your senior teammate handles the termination safety logic; you handle the detection.

Responsibilities

  • Build resource utilization data collection from cloud provider APIs
  • Apply idle classification rules across compute, storage, and database resources
  • Generate candidate idle resource lists with supporting evidence
  • Handle edge cases: intentionally idle resources, maintenance windows
  • Test classification accuracy against manually reviewed resource samples
  • Document idle detection rules and classification logic

Requirements

  • 1+ year of Python development with API integration experience
  • Basic familiarity with at least one cloud provider: AWS, GCP, or Azure
  • Understanding of resource types: EC2, RDS, S3, GPU instances
  • SQL skills for querying utilization metrics databases
  • Interest in cloud cost optimization and FinOps

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $1,500 learning stipend
  • Mentorship from senior cloud engineers
  • Save clients millions in wasted cloud spending

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Categories

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python aws docker sql fastapi

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python aws docker sql fastapi pandas

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