Direct-to-consumer furniture platform built on AWS and GCP
Resident is a furniture e-commerce business running on AWS and GCP infrastructure, with a tech stack split between Node.js/TypeScript backend (Express, Nest) and React frontend, backed by PostgreSQL and MongoDB. Active hiring across marketing, product, and data roles—with five director-level positions open—suggests simultaneous pushes on commerce platform scaling, a new data foundation, and AI adoption across customer experience workflows. Pain points cluster around conversion rate optimization, measurement gaps, and AI performance, indicating the company is mid-maturation in both analytics rigor and generative AI integration.
Notable leadership hires: Design Director, Director of Product, CRM Director
Resident designs and sells home furniture through direct-to-consumer channels, operating from Tampa, Florida with 201–500 employees. The company was founded in 2017. Their technical infrastructure spans AWS and GCP, with modern development practices (Kubernetes orchestration, SAST/DAST security scanning, TypeScript/Node.js stack). Current product work centers on the commerce core platform, e-commerce experience design, order lifecycle management, and a design system evolution. The organization is expanding advertising measurement and AI capability—including AI tool evaluation and CX journey automation—while managing growth across US and Israeli teams.
AWS, GCP, Kubernetes, Node.js, TypeScript, Express, Nest, React, PostgreSQL, MongoDB, and Python. Security tooling includes SAST and DAST. Data and analytics run on BigQuery and Google Analytics 4.
Tampa, Florida. The company was founded in 2017 and is privately held, with 201–500 employees.
Resident'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.