Self-clearing broker API powering embedded trading and investing apps
Alpaca operates as a self-clearing broker-dealer offering APIs for stocks, options, ETFs, and crypto trading. The stack—Go, Rust, C++, Kubernetes on GCP, plus Temporal and gRPC—reflects a systems-heavy focus on low-latency, distributed trading infrastructure. Active hiring across engineering (44 roles), product (22), and sales (17), combined with projects around institutional trading platforms, identity verification at scale, and securities/crypto app launches, signals aggressive expansion into enterprise and international markets.
Notable leadership hires: Head of Information Security, Compliance Director, Brokerage Operations Director, Team Lead Engineer
Alpaca is a US-registered broker-dealer providing infrastructure APIs for fintech platforms and institutions to embed trading, investing, and tokenization capabilities. The platform supports stocks, ETFs, options, fixed income, and crypto across 40+ countries, serving over 9 million brokerage accounts. Beyond API access, Alpaca delivers value-added services including fully paid securities lending, high-yield cash offerings, 24/5 trading, and Shariah-compliant investment options. The company operates a self-clearing model, meaning it settles trades directly rather than routing through a third party.
Core languages: Go, Rust, C++, TypeScript. Infrastructure: Kubernetes on GCP with Terraform. Data layer: PostgreSQL, Trino, Apache Iceberg, Redpanda. Workflows: Apache Airflow, Airbyte, Temporal. Observability: Grafana. Also uses DTCC integration and FedNow for settlement connectivity.
Current priorities: institutional trading platform, US securities and crypto trading apps, modern identity verification (global expansion), broker API product line, self-service AI onboarding, correspondent clearing, and automation of core workflows.
Alpaca'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.