AI-powered fraud and bot defense platform for enterprise account security
Arkose Labs operates a defense-in-depth platform protecting enterprises from account takeovers, bot attacks, and AI-powered fraud. The tech stack—Go, Python, Kubernetes, ScyllaDB, React—indicates a distributed, high-throughput architecture built for real-time threat detection at scale. Hiring is weighted heavily toward senior and director-level roles in sales and engineering, paired with multi-year strategic account plans and enterprise-wide platform adoption projects, signaling a shift from product expansion toward land-and-expand execution with large customers.
Notable leadership hires: Director of Marketing
Founded in 2016 and based in San Mateo, Arkose Labs provides account security and fraud prevention to Fortune 500 enterprises in financial services, technology, social media, and travel. The Arkose Titan platform unifies bot detection, device intelligence, email verification, API security, and behavioral biometrics through a single API, eliminating latency and vendor fragmentation. The company operates across 201–500 employees, with active hiring in the United States and India. Core pain points center on scaling test automation, automating threat response workflows, and reducing manual effort in fraud detection—challenges that align with the company's focus on productized automation capabilities.
Go, Python, Kubernetes, AWS/Azure, ScyllaDB, Istio, ArgoCD, Docker, React, JavaScript, Node.js. Mobile SDKs use React Native, Swift, and Kotlin. Testing uses Cypress, Selenium, and Appium.
Multi-year strategic account expansion, enterprise-wide platform adoption, Appium framework development, mobile SDK integration testing, CI/CD pipeline integration, and productized automation for threat detection and mitigation.
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Arkose Labs'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.