Mobile-first investment platform with fractional stock trading and AI-powered market insights
Toss Securities operates a Java/Kotlin-heavy backend (Spring Framework, Kafka, Elasticsearch) powering fractional stock trading and real-time market data. The tech stack reflects a fintech infrastructure play: Redis caching, Kafka event streams, Elasticsearch indexing, plus emerging RAG adoption signals an AI feature roadmap. Hiring is balanced across engineering, product, and data (14, 13, 10 roles respectively), with seniority skewed toward mid and senior levels—typical of a scaling fintech post-product-market fit.
Toss Securities is a South Korean investment platform launched in March 2021 that has built a mobile trading system targeting retail investors. The product enables fractional overseas stock trading, community-driven investing, and web-based trading, paired with AI-driven information tools to reduce friction in market research. The company operates 201–500 employees across engineering, product, data, security, and design. Current focus areas include high-availability architecture, new financial service launches, portfolio management, and post-merger integration, alongside active work on privacy certifications and disaster recovery.
Primary languages: Java, Kotlin. Frameworks: Spring Boot, Spring Cloud, Spring Framework. Data: Kafka, Elasticsearch, Redis, MySQL, MongoDB, Oracle, ClickHouse, HBase, Hadoop. Infrastructure: Kubernetes, Istio, ArgoCD, GoCD. Monitoring: Prometheus, Grafana. Currently adopting RAG.
High-availability architecture and automation, new financial service launches, portfolio management tools, M&A integration, disaster recovery process evaluation, and privacy/security certification maintenance.
Toss Securities'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.