CFTC-regulated exchange for trading event contracts on future outcomes
Kalshi operates a federally regulated exchange where traders take positions on whether future events will occur. Its stack pairs Rust and Go trading services with WebSockets and Kafka for real-time market data, backed by a multi-cloud footprint across AWS, GCP and Azure. Hiring tilts senior and spreads across engineering, finance and legal, while job posts point to corporate development work: an M&A pipeline, partnership evaluation and post-deal integration.
Kalshi is a New York-based exchange, founded in 2019, that lists event contracts. These let traders take a yes-or-no position on whether a future event will happen, including sports outcomes and other economically relevant events. The privately held company employs 51–200 people, and all of its hiring is in the United States. Its products include a consumer trading app built with Flutter, an API for programmatic trading, and an offering called Kalshi Prime. Compliance and legal functions support its regulated status with the CFTC.
Kalshi uses Rust, Go, Python and Java, plus Flutter for mobile. It streams data with Kafka and WebSockets, stores data in PostgreSQL, Snowflake and Redshift, and runs on Kubernetes across AWS, GCP and Azure.
Job posts point to scaling Kalshi Prime and expanding API infrastructure. They also mention a sports market listing pipeline, a portfolio management rework, alerts and watchlists, and building an M&A pipeline.
Kalshi is headquartered in New York, New York. The company was founded in 2019, has 51–200 employees, and hires only in the United States.
Other companies in the same industry, closest in size
Kalshi's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.