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Kalshi

Software Engineer, Trading Platform

New York Office$200k–$280kfulltimemidAdded 1 month ago

About this role

Join Kalshi's engineering team to build core infrastructure for a next-generation prediction markets platform. You'll work on critical systems including order matching, trading APIs, clearing infrastructure, and market integrations, with significant ownership and impact on a rapidly growing financial exchange.

What you'll do

  • Design and optimize order matching algorithms and trade execution systems
  • Build high-performance data feeds and trading APIs for clients
  • Develop clearing systems with focus on availability, margining, and collateral management
  • Lead integrations with external market makers, brokers, and financial institutions
  • Stress test and optimize critical systems for performance and reliability
  • Design new market structures and collaborate directly with customers on product features

What they're looking for

  • Software engineering (4+ years experience)
  • Relational databases and transaction management
  • Highly concurrent systems design
  • Large-scale system architecture and optimization
  • Project leadership and technical problem-solving
  • Process and tooling development for engineering efficiency
  • Financial systems or FIX API experience (bonus)
  • Fast shipping and iterative product development

Benefits

  • Salary: $200,000–$280,000 annually plus equity
  • Meaningful ownership of entire systems and features
  • Minimal hierarchy with high visibility of impact
  • Opportunity to work on greenfield financial infrastructure
  • Direct customer interaction and product collaboration
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Kalshi

Kalshi builds a prediction market trading platform and exchange infrastructure. The company is hiring frontend engineers, backend engineers, site reliability engineers, infrastructure engineers, and mobile engineers to scale its rapidly growing financial trading systems.

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Likely interview questions

  • Walk us through your experience designing or optimizing order matching algorithms and data structures for high-performance systems. What were the key performance bottlenecks you encountered?
  • Describe a time you led a large project with long-term impact on a system or team. How did you approach planning, prioritization, and execution?
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