Original listing text, shown exactly as published by the company.
The Role
We're building an AI assistant that helps developers understand and grow their subscription revenue. It lives in Slack today and is expanding to our dashboard and API. It can pull real-time data, evaluate experiments, debug integrations, and explain what's happening in your app using natural language. We see a future where the majority of a user's interactions are either intermediated or automated by our agent.
We're a team that's historically built deterministic CRUD systems, and we need an engineer who can build the foundational agent infrastructure that everything else runs on: orchestration, tool execution, context management, evaluation, and the trust layer that lets us give an agent increasing autonomy over things that matter.
About you
- You have 5+ years of experience shipping production systems.
- You have hands-on experience building with LLMs — not just prompting, but building the systems around them: tool use, structured output, context management, evaluation, orchestration.
- You have strong backend fundamentals. You've built systems that need to be reliable, observable, and secure.
- You are comfortable with ambiguity. This is an early-stage product inside a growth-stage company. The architecture is still being figured out.
- You are self-directed. You figure out what needs to be built, build it, and ship it.
- You collaborate well with others and can communicate effectively in a fully-remote culture.
Bonus
- Experience with OpenAI/Anthropic APIs specifically.
- You've built agents that other people use.
- Experience with evaluation and observability frameworks (Langfuse, Langchain, etc).
- Familiarity with subscription business models, app stores, or developer tools.
- You've built Slack integrations or other conversational interfaces.
- Contributions to open-source AI/ML tooling.
In the first month, you'll
- Ship your first agent feature and get familiar with the architecture, tool ecosystem, and how Rico talks to RevenueCat's APIs.
- Identify the biggest reliability or performance gap and start fixing it.
- Meet with the team, get set up with repos, dev environment, and debugging tools.
- Familiarize yourself with RevenueCat dashboards, logging, debugging tools, cloud providers, infrastructure management and general architecture.
Within the first 3 months, you'll
- Launch a brand new agentic feature to tens of thousands of developers.
- Own a core infrastructure area — orchestration, eval pipeline, tool framework, or the trust/permissions layer.
- Be able to scope and work on projects self-sufficiently.
- Learn the basics of incident response and be part of the on-call rotation.
Within the first 6 months, you'll
- The agent is measurably more reliable, faster, and capable because you're here.
- You've built infrastructure that the rest of the team ships agents with.
- Review code, create proposals, and contribute to architectural discussions.
- Have shipped a major product or feature.
Within the first 12 months, you'll
- RevenueCat is an AI-native company. You built the engine underneath it.
- Know all the major components of our agent system and be able to debug complex issues.
- Have your own initiatives for improving our agent products, understanding the current issues and priorities.
- Mentor other engineers joining the team.
