Growth Engineer

At Composio, we are building infrastructure that allows agents to communicate with the tools you use for work including Github, Gmail, Notion, Salesforce, etc. We are a small team of engineers wrangling problems from context to search, that help us provide the most capable bridge between your agents and your tools.

We raised a $25M Series A from Lightspeed with some incredible angels like Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of Hubspot), Gokul Rajaram. Beginning of this year we 3x our ARR, our customer range from your friends in the YC batch to Wabi, Glean, Zoom and many more.

The role

This is a full-stack engineering role focused on growth. You'll build the features, pages, and systems that drive awareness, activation, and retention - and you'll own them end-to-end from concept through measurement.

The work looks like: shipping a new onboarding flow in a day, standing up a backend service to support a referral system, building an internal dashboard to understand where users drop off, and then deciding what to build next based on what the data says.

The goal is to maximize shots on goal. You scope ruthlessly to find the smallest version of an idea that gets real signal, ship it, instrument it, and let usage data tell you what deserves more investment. When something hits, you build it out properly - architected well enough that it can be handed off or scaled up without a rewrite. When something doesn't, you kill it and move on.

What you'll actually do

• Ship features across the full stack - frontend pages, backend services, data pipelines - whatever the problem needs
• Context-switch across codebases without losing speed
• Design and implement backend systems to support growth features, not just wire up UIs
• Set up tracking, build dashboards, write queries, and dig into funnels to understand what's working
• Make product decisions independently once you have a direction and a target
  
  

What we're looking for

If you're very good, nothing here is a hard "must" - but this is what the work demands, and you'd be expected to learn.

• Full-stack engineer who ships fast. You're equally comfortable building a polished frontend page and designing a new backend service. You don't wait for someone else to build the other half.
• Strong bias toward action. You operate with a direction, not a detailed spec. You'd rather ship something incomplete that generates signal than spend a week on something that might not matter. You don't ask for permission to start building.
• Ownership and agency. You take a goal - "improve activation by X" - and independently figure out what to build, build it, and measure whether it worked. You don't need a PM to hand you tickets or a manager to check your work.
• Comfortable with data. You can write SQL (or figure it out), set up event tracking, build dashboards, and form hypotheses from what you see. You let data inform your next move, not just intuition.
• Fluent in the AI ecosystem. You're building with LLMs and you follow what's happening in the space. When something new ships, you're already thinking about what to do with it.
  
  

Nice to have

• Experience with PostHog, Snowflake, or similar analytics/warehouse tools
• Experience building or maintaining ETL pipelines
• Prior growth engineering or product engineering at a startup
• You've built something that got traction - on purpose or by accident
• Presence in the AI community (open source, writing, building in public)
• You've started a company or run a meaningful side project