Job Description
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 customers range from your friends in the YC batch to Wabi, Glean, Zoom and many more.
What you'll do?
ship growth experiments across the stack - landing pages, onboarding flows, backend services, data pipelines, dashboards, and internal tools
scope ruthlessly to get signal fast, then either kill the idea or build it properly
instrument product funnels, write queries, build dashboards, and use data to decide what deserves more investment
own activation and retention problems without waiting for a PM to turn them into tickets
work with marketing, product, and engineering to turn distribution ideas into shipped product
use agents and Composio itself to make your own workflow faster
"Must haves"
if you are very good, nothing is a must per-se
full-stack engineer
you are comfortable shipping polished frontend and backend systems
you can context-switch across codebases without losing speed
growth taste
you know the difference between a cheap experiment and a sloppy product
you would rather ship a narrow signal-generating version today than a perfect unknown version next week
data comfortable - you can write SQL or learn quickly, set up tracking, and reason from messy funnel data
ai native - you build with LLMs and keep up with what is happening in the ecosystem
owner - you take a goal, decide what to build, ship it, and measure whether it worked
human - you build trust and admit what you do not know
Optional
experience with PostHog, Snowflake, or similar analytics tools
prior growth engineering or product engineering at a startup
built something that got real traction
presence in the AI community through open source, writing, or building in public