Arcade

About the Company

Arcade is building the world's first AI physical product creation platform, where imagination becomes reality. Our platform lets anyone design, purchase, and sell custom, manufacturable products using natural language and generative AI. We believe everyone should have the power to create physical goods as easily as they post online, and we're building the infrastructure to make that real. We've raised $42M from a world-class group of investors, including Reid Hoffman, Forerunner Ventures (Kirsten Green), Canaan Partners (Laura Chau), Adverb Ventures (April Underwood), Factorial Funds (Sol Bier), Offline Ventures (Brit Morin), Sound Ventures (Ashton Kutcher), Inspired Capital (Alexa von Tobel), and Torch Capital (Jonathan Keidan). Our angel investors include Elad Gil, Ev Williams, Marissa Mayer, Sara Beykpour, Kayvon Beykpour, Anna Veronika Dorogush, Eugenia Kuyda, David Luan, Sharon Zhou, Kelly Wearstler, Karlie Kloss, Colin Kaepernick, Christy Turlington Burns, and Jeff Wilke. Arcade is headquartered in San Francisco's Presidio and led by serial entrepreneur Mariam Naficy (Minted, Eve), and a founding team with deep experience in generative AI, design systems, and supply chain. We're pioneering a new category at the intersection of AI, personal expression, and on-demand manufacturing, and we're building fast.

Listed Jobs

Company Name

Arcade

Job Title

Software Engineer

Job Description

Job title: Software Engineer Role Summary: Design, build, and maintain scalable back‑end systems that enable real‑time, generative AI workflows for custom physical product creation. Own critical infrastructure—from model orchestration and caching to API design and observability—and collaborate with AI research, product, and design to deliver new user experiences. Expactations: Deliver high‑quality, reliable services at speed; move swiftly from prototype to production; own features end‑to‑end; maintain clear, maintainable code in a fast‑moving, high‑agency environment; prioritize performance, latency, and stability. Key Responsibilities: - Design and implement scalable back‑end architecture for LLM inference, prompt orchestration, and agentic workflows. - Own core user‑facing infrastructure: REST/GraphQL APIs, job queues, caching layers, observability, and deployment pipelines. - Collaborate with AI research, product, and design to transition new generative capabilities into production. - Build primitives for text‑to‑product creation: model pipelines, tool integrations, retrieval flows, and evaluation frameworks. - Continuously optimize system performance, latency, and reliability of inference‑heavy workloads. - Participate in code reviews, design reviews, and knowledge sharing within a high‑trust, high‑velocity engineering culture. Required Skills: - Strong back‑end and infrastructure engineering fundamentals. - Proven ability to own production systems that serve real users or data. - Experience with Python, Django or FastAPI, Kubernetes, Docker, GCP, Google Pub/Sub, and similar cloud infrastructure. - Hands‑on expertise with LLM pipelines, model orchestration, prompt tooling, or related generative AI technologies. - Excellent debugging, performance tuning, and system‑design capabilities. - Ability to prototype quickly and ship production‑grade code under tight timelines. Required Education & Certifications: - Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Physics, Mathematics, or a related technical field.

San francisco, United states

On site

23-12-2025