Sr. Staff Engineer

About the role

Polymarket is the world's largest prediction market platform. We enable individuals to express views on real-world events by trading on outcomes across politics, economics, sports, culture, and current affairs. Built as a peer-to-peer marketplace with no centralized "house," Polymarket aggregates diverse opinions into transparent, market-based probabilities that reflect collective expectations about the future. We're growing fast, both in terms of volume ($21B traded in 2025) and adoption as an alternative news source. Our ambition is to become a ubiquitous beacon of truth in global media and we need your help adding fuel to the fire. 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. This role is responsible for ensuring those systems are robust, scalable, and aligned with the company's rapid growth trajectory.

Key facts

What you'll do

• 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.
• Own the technical decisions that define how user behavior data is captured, transformed, and surfaced across the product analytics stack.
• Partner closely with product and data science to define metrics that matter and ensure experiments are built with measurement rigor from the start.
• Drive standards for code quality, observability, and reliability across the growth engineering domain so that new features can be launched with confidence.
• Identify bottlenecks in the data pipeline and experimentation workflow, then implement fixes that improve speed, accuracy, and developer ergonomics.
• Design and implement abstractions that allow other teams to run experiments and analyze results without deep expertise in instrumentation or infrastructure.
• Evaluate new martech and analytics tools, conducting cost-benefit analyses and proposing replacements or integrations when appropriate.
• Maintain a production-grade mindset, ensuring that every feature you ship is monitored, alertable, and maintainable over the long term.

Requirements

• 10+ years of experience spanning full-stack development, data and analytics infrastructure, and martech systems.
• Production-level expertise in Golang and TypeScript. You write both regularly and know where each one has edges.
• A track record of designing analytics and data pipelines that teams rely on in production, not side projects or internal dashboards nobody checks.
• Hands-on experience building and shipping ML systems. You've taken models past experimentation and into production.
• Strong systems thinking and the judgment to make architectural calls between refactor and rewrite, talking through real trade-offs rather than defaulting to a preference.
• Fluency with AI-assisted development. You use these tools every day and you're faster and more accurate because of it.
• Experience setting technical direction for a growth or data team, with high-stakes calls made under ambiguity and limited oversight.
• (Plus) Prior experience on a marketplace, fintech, or consumer product with meaningful user scale.
• (Plus) Familiarity with prediction markets, financial products, or real-time data systems.
• (Plus) People management experience. You don't need it for this role, but it's useful context.

Nice to have

The preferred items listed in the requirements above are already captured and do not need restatement here. No additional preferred qualifications are specified beyond what is included in the requirements section.

Practical notes

This role is fully remote, with no requirement for travel or specific visa sponsorship details provided in the source material. The engagement is full-time, and the work is expected to be conducted during standard working hours as determined by the successful hire and their manager. There are no explicit deadlines for application or onboarding communicated in the source text.