The Growth Engineering team owns the systems that determine how people find Polymarket, what they do when they get here, and whether they come back. That means analytics infrastructure, martech integrations, experimentation frameworks, and the full-stack features that move conversion and activation numbers. It's a small, high-output team where the work is technical and the stakes are real
We're hiring a Sr. Staff Engineer to be the technical foundation of that team. You'll own architecture decisions that affect how the entire team measures and ships work. You'll build and maintain the data pipelines that growth depends on, set the standard for how experiments are designed and evaluated, and ship full-stack features end-to-end without waiting on anyone else. This is not a coordination role. You will be writing code daily
This hire matters because growth at Polymarket is accelerating and the infrastructure underneath it needs to scale with it. The person in this role will have direct influence on what gets built, how it gets built, and what gets retired. You'll do that as a senior IC with the trust and autonomy to make high-stakes calls, not someone who needs sign-off at every step
Build and maintain Go-based data pipelines that power growth analytics, from event ingestion to reliable reporting that the team actually trusts
Audit existing martech integrations, identify what's underperforming or redundant, and replace or retire tooling with clear-eyed judgment
Architect and ship experimentation infrastructure that lets the team run clean A/B tests, measure results accurately, and move fast without breaking measurement
Ship full-stack growth features in Go and TypeScript, owning the work from backend service to frontend implementation without handing off
Bring ML where it adds real value, including personalization, predictive modeling, and experiment analysis, and build those systems into production, not just prototypes
Review experiment designs and code from other growth engineers, raising the quality of what ships and how the team thinks about building
Use AI tools daily and seriously, applying them to accelerate your own output and set a higher bar for how the team works