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Sports Operations Engineer

Job in New York, New York County, New York, 10261, USA
Listing for: Kalshi
Full Time position
Listed on 2025-12-16
Job specializations:
  • IT/Tech
    Data Engineer, Systems Engineer
Job Description & How to Apply Below
Location: New York

Kalshi has defined a new category: prediction markets. Kalshi allows people to trade on the outcome of any events and turn any question about the future into a financial asset. Kalshi fought for years and legalized prediction markets in the US for the first time in history. Kalshi is currently the fastest growing financial market in America, and has thousands of markets across politics, economics, financials, weather, tech, AI, culture and more.

We believe prediction markets have the potential to be the largest financial market because they turn anything into a financial position.

Our vision: well… build the largest financial market on the planet.

Our mission: bring more truth to the world through the power of markets.

Building a new category is hard… like really hard. But it s beautiful and deeply fulfilling. Our culture is simple: we hire really talented people, work really hard, and enjoy the climb. We are looking for ambitious and exceptional people to join our (relatively small) team to help us build the next generation of financial markets.

Role Roadmap

As a Sports Operations Engineer at Kalshi, you ll be the technical force behind our sports markets infrastructure. You ll build and maintain the automation systems that power thousands of sports markets across all major leagues. This role combines deep sports knowledge with strong engineering skills to create scalable solutions for market listing, monitoring, and settlement. We re scaling rapidly, which means your role will evolve and grow with the company;

your initial responsibilities will include:

Automation Development: Design and build Python automation scripts that list, update, and determine sports markets ate intelligent systems that handle pre-game, in-play, and futures markets across NFL, NBA, MLB, NHL, MLS, NCAA, and international competitions without manual intervention.

Data Pipeline Architecture: Build robust data pipelines that ingest, process, and structure large volumes of sports data from multiple feeds. Design systems that handle real-time game data, player statistics, injury reports, weather updates, and official league sources while maintaining data integrity and low latency.

DAG & Workflow Orchestration: Implement and maintain complex DAGs for orchestrating market operations workflows. Design fault-tolerant systems that handle dependencies between data ingestion, market creation, live updates, and settlement processes across thousands of concurrent sporting events.

Scheduled Job Management: Develop and maintain cron jobs and scheduled tasks that automatically list markets at optimal times, update odds based on market conditions, and settle markets immediately after game completion. Ensure reliable execution during high-volume periods like NFL Sundays.

Internal Tooling Ownership: Own and evolve internal tools used by the Market Operations team. Build intuitive interfaces for market management, settlement verification, and operational monitoring. Gather requirements from operators and continuously improve tooling to increase efficiency and reduce errors.

Sports Logic Implementation: Translate complex sports rules and edge cases into code. Build systems that understand overtime rules, tiebreakers, playoff scenarios, and sport-specific nuances. Implement logic for handling postponements, suspensions, protests, and stat corrections across different leagues.

Real-time Processing Systems: Create systems that process live game feeds and trigger appropriate market actions in real-time. Build monitoring and alerting systems that detect anomalies, data discrepancies, or unusual game situations requiring intervention.

Settlement Automation: Develop automated settlement systems that accurately determine market outcomes based on official results. Implement verification layers that cross-reference multiple data sources and flag potential discrepancies for review.

Performance Optimization: Continuously improve system performance to handle increasing market volumes. Optimize database queries, implement caching strategies, and ensure our infrastructure scales smoothly during peak trading periods.

Cross-functional Engineering: Collaborate with…

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