Full Stack Engineer

Raindrop is building Sentry for AI Agents, providing alerts for hidden issues and successes in AI agents. It helps AI engineers quickly identify and fix misbehavior by linking alerts directly to events, enabling them to understand root causes from conversations or traces. The platform learns the unique issues of each AI agent, from presets like Laziness or Task Failure, to automatically tune itself to specific agents, processing millions of events to track issues and topics across production data. As part of the early team, you'll play a fundamental role in shaping the company, from strategy and product decisions to scaling the team and shaping the future of AI agents.

Must Have

• Build out a world-class product servicing millions of requests a day.
• Architect, implement, and scale the application.
• Quick iteration without compromising on quality.
• Proven experience setting up and scaling applications.
• Knows how to balance short-term and long-term speed.
• Cares about building well-designed products.
• Willing to do whatever it takes to solve a problem.
• Must be in person in San Francisco (or willing to move).

Good to Have

• Leverage the latest in ML/Interpretability research (e.g. SAEs) to drive customer insights.
• Interest in AI products and tools (ideally experience building these or an avid user).
• Growth mindset.

Raindrop is building Sentry for AI Agents.

AI engineers use Raindrop to get alerts about hidden issues and successes in their AI agents. Raindrop sends alerts when AI agents misbehave and links straight to the events, so AI engineers can dig into the conversations or traces, understand the root cause, and fix it, fast.

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 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 AI chatbots and agents 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.

With one click of a button, AI engineers start tracking issues or topics across 100% of your 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.

Our Investors

We’re backed by incredible investors including Y Combinator, James Tamplin (Founder of Firebase), Guillermo Rauch (Founder of Vercel), Balaji Srinivasan (Former CTO @ Coinbase), Matt MacInnis (COO @ Rippling), and amazing folks from Figma, Scale, OpenAI, Worldcoin, Apple, and more.

Your Focus

• Build out a world-class product - servicing millions of requests a day + growing.
• Architect, implement, and scale our application
• Quick iteration without compromising on quality
• Stretch: Leverage the latest in ML/Interpretability research (e.g. SAEs) to drive customer insights

Ideal Candiate

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