What You’ll Do

Build markets automation systems: Design and implement pipelines that automate market creation, parameter configuration, and lifecycle management across thousands of concurrent markets.
Engineer resolution infrastructure: Build reliable, data-driven resolution systems that integrate with external oracles, news feeds, sports APIs, and real-world data sources to settle markets accurately and on time.
Design event-driven automation: Build robust event processing systems that detect and respond to real-world triggers across politics, sports, finance, and current events using messaging and streaming platforms (Kafka, Pulsar, RabbitMQ).
Own reliability & operations: Reinforce correctness, availability, and scalability across markets systems, and participate in diagnosing and resolving production issues.
Collaborate cross-functionally: Work closely with engineers across product, infra, data, and markets operations to ensure tight integration between the markets layer and the broader platform.
Contribute to code quality: Participate in code reviews, design discussions, and architectural decisions to maintain a high bar for engineering excellence.

What We’re Looking For

4–7+ years of professional backend development experience, with strong proficiency in Python or Go (preferred), or another language such as Rust or Java.
Solid understanding of distributed systems, data pipelines, and event-driven architecture; comfortable owning systems end-to-end in production.
Experience building automation systems, workflow orchestration, or integrations with third-party data sources and APIs.
Comfortable debugging complex systems on Linux and taking ownership of correctness and reliability.

Nice to have:

Experience with prediction markets, financial data, or real-world event detection systems.
Familiarity with external data integrations — news feeds, sports APIs, oracles, or similar real-world data sources.
Production experience with Kafka, Pulsar, or similar streaming platforms at scale.
Experience deploying systems in cloud environments (AWS/GCP) and using containers.