Backend Engineer

Raindrop Monitoring Platform

Raindrop is the monitoring platform for AI agents. Engineering teams at Fortune 100s and the fastest-growing AI companies use it to catch silent failures in production. When an agent misbehaves, Raindrop alerts the team, links to the trace, and surfaces the root cause so they can fix it fast. With Raindrop 2.0 (Self-Healing Agents), the loop closes itself: your coding agent fixes it, and the fix becomes an eval to prevent regressions.

Why It Matters

AI agents fail constantly in ways both hilarious and terrifying. Regular software throws exceptions. But AI agents fail silently, leaving engineers with almost no visibility into how their agents are actually performing.

The current status quo is sifting through millions of logs and trying to debug flaky evals that just aren't matching real world results. Evals are like unit tests, they confirm your model got specific test cases right. But in the real world agents call thousands of tools, run for hours, and encounter millions of unpredictable actions.

That's where Raindrop comes in. It learns the unique shape of each AI agent's issues. Starting from presets like Laziness, Forgetting, or Task Failure, to automatically tuning itself to each agent and discovering unknown unknowns.

With one click of a button, AI engineers start tracking issues or topics across 100% of their production data. They can see frequency over time, how many users are affected, relevant properties and more.

In order to process hundreds of millions of events, we gradually train small, custom models, private to each company, that learn to uniquely understand how their product is used.

As part of the early team, you'll play a fundamental role in shaping the company - from making strategy and product decisions, to helping scale the team, to shaping the future of AI agents.

Your Focus

• Build out world-class infrastructure - servicing millions of requests a day + growing.
• Architect, implement, and scale the application
• Quick iteration without compromising on quality
• Deeply understand the customer

Ideal Candidate

• Knows how to balance short-term and long-term speed
• Proven experience scaling applications
• Interest in AI products + tools (ideally experience building these or an avid user)
• Growth mindset
• Willing to do whatever it takes to solve a problem
• Must be in person in San Francisco (or willing to move)