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Raindrop

Monitors production AI agents for failures

Founding Sales Engineer

Pre-Sales Solution EngineeringPosted on Nov 11
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Strong engineering ability to read a codebase and build a working prototype quickly.
  • Sales instincts and understanding of deal progression, including when to lead and when to let the account executive run the room.
  • Experience selling developer tools or infrastructure products to engineers, ideally as an early Sales Engineer who built the playbook.
  • Understanding of how AI agents fail in production and ability to explain those failures to the people building them.
  • Ability to use and build AI agents and tools.

Responsibilities

  • Partner with account executives from discovery through close and own the technical side of deals.
  • Answer technical buyers' questions and demonstrate how Raindrop solves their problems.
  • Build prototypes and integrations for customer requests, and ship them into the product when possible.
  • Determine when a customer request needs a deeper backend or machine learning change and involve the appropriate engineers.
  • Bring patterns from deals back to the team and provide recommendations on what to build.
  • Work closely with leadership and own high-impact work.
  • Conduct technical discovery and demonstrate Raindrop to engineering teams.
  • Run proofs of concept and evaluations end to end so customers can see value before signing.
  • Identify customer requests that indicate broader product needs, prototype solutions, and help incorporate them into the platform.
  • Create demos, playbooks, and technical content for the sales team.

About the Company

Raindrop

Monitors production AI agents for failures

Raindrop monitors production AI agents for silent failures such as wrong answers, lost context, persona drift, or stuck loops. It works by adaptive alerting, tracing conversations, and deep searching production data and A/B tests, with Raindrop Simulations to replay traffic on every PR. It differentiates itself by targeting production-time, hard-to-detect AI issues related to context and behavior history, using replayable analysis alongside alerts. Its goal is to help teams deploy AI agents more reliably by catching hidden defects early and maintaining correct behavior and context in production.

Company size
11-50
Company stage
Series A
Total funding
$50M
Headquarters
San Francisco, CA
Founded
2023

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