OfferUp operates a consumer mobile marketplace connecting buyers and sellers across used goods, jobs, services, and rentals. The tech stack reveals infrastructure maturity—Java microservices on AWS, Kubernetes orchestration, BigQuery + Databricks for analytics—paired with emerging AI tooling (LangChain, LangGraph, Gemini, SageMaker). Active projects around production RAG pipelines and agentic workflows signal a shift toward AI-driven discovery and seller automation, while simultaneous investment in legacy system replacement and microservices redesign suggests the company is refactoring core infrastructure to handle scale.
OfferUp is a mobile-first C2C marketplace founded in 2011, based in Bellevue, Washington, and serving millions of users across the United States. The platform spans multiple verticals: secondhand goods, local jobs, professional services, and home rentals, all accessible through a mobile app designed for local discovery. The company operates with a mid-market team (201–500 employees) structured around engineering, product, data, and business operations. Current hiring across engineering, product, and data roles—with emphasis on mid-level and principal-level hires—reflects active scaling of technical infrastructure and experimentation capabilities.
OfferUp runs on Java microservices deployed on AWS with Kubernetes, uses React and React Native for mobile, and relies on BigQuery, Databricks, and SageMaker for data and ML. Recent additions include LangChain, LangGraph, and Gemini for AI-driven features.
OfferUp is building production RAG pipelines for intelligent discovery, agentic workflows for seller automation, and redesigning core microservices for real-time operations. The company is also replacing legacy systems and developing a self-serve acquisition flywheel for business sellers.
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OfferUp'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.