Proprietary trading firm with funded account program for retail futures traders
Tradeify operates a three-stage trader funding model—challenge, simulated account, then live capital—built on a polyglot stack (React, Next.js, Python, Node.js, C#, Go) connected via Kafka, NATS, and Pulsar. Current hiring skews heavily toward marketing (5 roles) and support (3 roles) against one engineering opening, while pain points center on content velocity, trader inquiry volume, and real-time market risk monitoring—suggesting the product is hitting adoption constraints faster than internal tooling can scale.
Notable leadership hires: Marketing Measurement & Analytics Lead
Tradeify is a proprietary trading firm that funds retail traders through a structured three-step program: an initial trading challenge, a simulated funded stage, and a live funded account for successful traders. The platform provides automated performance journaling, trader support, and risk management infrastructure. Based in Miami with 51–200 employees, Tradeify serves individual traders seeking capital access and is currently scaling support operations while building out measurement and risk automation capabilities.
Frontend: React, Next.js, Vue. Backend: Python, Node.js, C#, Go. Data: PostgreSQL, MySQL, Redis, MongoDB, ClickHouse, TimescaleDB. Infrastructure: Docker, Kubernetes. Messaging: Kafka, NATS, Apache Pulsar. Customer tools: Zendesk, Intercom, HubSpot.
Trader-facing learning center, beta features, scalable measurement foundation, attribution modeling, dashboards, automated alerts, risk tooling, knowledge base, and support workflow improvements. Current blockers include content publishing delays, high trader inquiry volume, and real-time market risk monitoring.
Tradeify'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.