Description review

Senior Software Engineer, Agents

RevenueCat · EMEA, LATAM, Canada, USA · back to the listing

HR standards

52/100

needs work

Title ↔ description

83/100

solid

Reads as

Backend Engineer

88% confident

What this role officially is

software developer — ESCO, the EU occupation classification

Software developers implement or program all kinds of software systems based on specifications and designs by using programming languages, tools, and platforms.

Also known as: application developer, application programmer, solutions developer, programmer, software specialist, application software developer

How others title the same work

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Startups

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What the listing never says

  • 33 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

RevenueCat removes the headaches of building and scaling in‑app subscriptions. Since graduating from YC’s S18 batch we’ve grown into the default monetization platform for mobile: we’re in >40% of newly shipped subscription apps, we process $12B+ in annual purchase volume, and we help everyone from a solo dev in Brazil to the OpenAI mobile team understand and grow their revenue.

We’re a remote‑first crew of 150+, spread across 25+ countries, and guided by values we actually practice: Customer Obsession, Always Be Shipping, Own It, and Balance. If you want your work to touch hundreds of millions of end‑users (and help the developers behind them get paid), you’ll fit right in.

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.

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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.

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You are comfortable with ambiguity. This is an early-stage product inside a growth-stage company. The architecture is still being figured out.

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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:

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Experience with OpenAI/Anthropic APIs specifically.

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You've built agents that other people use.

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Experience with evaluation and observability frameworks (Langfuse, Langchain, etc).

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Familiarity with subscription business models, app stores, or developer tools.

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You've built Slack integrations or other conversational interfaces.

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Contributions to open-source AI/ML tooling.

In the first month, you'll:

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Ship your first agent feature and get familiar with the architecture, tool ecosystem, and how Rico talks to RevenueCat's APIs.

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Identify the biggest reliability or performance gap and start fixing it.

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Meet with the team, get set up with repos, dev environment, and debugging tools.

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Familiarize yourself with RevenueCat dashboards, logging, debugging tools, cloud providers, infrastructure management and general architecture.

Within the first 3 months, you'll:

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Launch a brand new agentic feature to tens of thousands of developers.

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Own a core infrastructure area — orchestration, eval pipeline, tool framework, or the trust/permissions layer.

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Be able to scope and work on projects self-sufficiently.

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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.

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You've built infrastructure that the rest of the team ships agents with.

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Review code, create proposals, and contribute to architectural discussions.

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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.

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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.

What we offer:

•
Competitive equity in a fast-growing, Series C startup backed by top-tier investors, including Y Combinator

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10-year window to exercise vested equity options

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Fully remote and flexible work environment

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4-5 weeks of suggested time off annually for mental, physical, and emotional recharge

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$2,000 USD for workspace setup and $1,000 USD annual stipend for continuous learning

Curious about the interview process? Discover more in our blog post about how we hire and learn tips to help you succeed.

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 16 points (from 68 before penalties). Reviewed 21 Sep 2026.