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AI API Usage Anomaly Detection Developer

Hudson Larsson

Full-time · Job · Los_Angeles

About the role

When an API client suddenly sends 10x more requests than usual, is it a successful product launch or a runaway script that's about to blow through their rate limit and crash our infrastructure? When a client's error rate jumps from 2% to 15%, is it their bug or ours? Our usage anomaly detection system answers these questions automatically, alerting both clients and our ops team before problems escalate. You'll build the anomaly detection models that learn normal usage patterns for each API client — request volume curves, error rate baselines, endpoint distribution, and payload size profiles — and flag deviations that warrant attention. The system monitors 890 million requests per month across 200+ clients, so the detectors need to be efficient and the alerts need to be precise. The platform reliability team is four engineers. You'll start with the volume anomaly detector, which is the most straightforward statistically, and progress to more nuanced detectors as you learn the domain. Your senior teammate handles the alerting and escalation logic; you'll provide the anomaly signals.

Responsibilities

  • Build usage anomaly detection models for API request patterns
  • Learn per-client baselines for volume, error rates, and endpoint distribution
  • Design alerting thresholds that balance sensitivity with false alarm rates
  • Monitor detection quality across 200+ API clients
  • Investigate flagged anomalies to refine detection rules
  • Document anomaly patterns for the reliability team knowledge base

Requirements

  • 1+ year of Python development with data analysis experience
  • Basic understanding of statistical anomaly detection concepts
  • Familiarity with SQL for querying usage data
  • Interest in API infrastructure and reliability engineering
  • Systematic approach to investigating data patterns

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $1,500 learning stipend
  • Mentorship from senior reliability engineers
  • Work on infrastructure handling 890M monthly requests

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python sql docker aws pandas statistics

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