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Sazabi

AI-native observability platform enabling debugging

Customer Support Lead

Customer SupportConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • The candidate must have strong technical intuition and be able to debug issues rather than merely route tickets.
  • The candidate must have strong communication skills, including clear, fast, and empathetic communication.
  • The candidate must demonstrate high ownership by solving problems through completion.
  • The candidate must be comfortable working directly with developers and understanding their workflows.
  • The candidate must be able to thrive in ambiguity without rigid support processes.

Responsibilities

  • Serve as the front line of Sazabi by helping users get value quickly.
  • Debug real customer issues using Sazabi itself.
  • Turn user pain into product insights and improvements.
  • Build lightweight systems for support, onboarding, and customer success.
  • Create documentation, guides, and content that scale support.
  • Work closely with engineering to resolve issues and ship fixes.

Desired Qualifications

  • Experience in developer tools support or early-stage startups.

About the Company

Sazabi

AI-native observability platform enabling debugging

Sazabi provides an AI-native observability platform designed for fast-moving engineering teams. It aims to simplify production monitoring by making observability accessible to all developers, not just infrastructure specialists. The product centers on conversational debugging, autonomous alerts that require no setup, and AI-powered analysis of large volumes of unstructured log data to reconstruct metrics and traces. It integrates with major AI coding agents and uses agentic anomaly detection to proactively surface only critical issues. Unlike traditional dashboards that rely on the three pillars of logs, metrics, and traces, Sazabi promotes the idea that logs can be enough to diagnose problems and focuses on a chat-like, question-driven interface to debug systems. The goal is to become the default observability solution for the AI era, reducing cognitive load and alert fatigue while speeding up root-cause analysis and incident response for engineering teams.

Company size
11-50
Company stage
Seed
Total funding
$8.1M
Headquarters
San Francisco, CA
Founded
2025

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