Arcade.dev is the secure action layer that authorizes, executes, and governs actions taken by production AI agents.
Everyone's building AI agents, but almost nobody gets them to production. Building an impressive demo is easy. Building an AI agent that can securely take action inside enterprise systems is hard. The moment an agent accesses customer data, executes a workflow, or makes changes on behalf of a user, authorization, governance, and trust become the real engineering challenge. Arcade is the MCP runtime that gives agents the power to do both seamlessly. We connect agents to the systems they act in, then give each one a permission slip and a paper trail - proof of what it's allowed to do, and a record of what it did. That's what makes AI safe to turn loose: real actions, on real systems, already shipping inside Fortune 100 companies. The Revolution Needs You Every AI app needs agentic tools that let AI models take real actions. Without tools, AI can only chat. With tools, AI can actually do things. We're building the definitive tools catalog, actions platform, and governance model that will unlock AI's true potential. Think Zapier for AI Actions. Think Auth0 for AI. Think really big. As Arcade's first designer, you'll build the UX/UI function from scratch. You start with the Dashboard — the surface where customers decide whether to trust their agents with real systems. From there, you shape whatever comes next: MCP Apps, and the surfaces nobody has named yet. Why This Is The Opportunity of a Lifetime - Traction: Real deployments with Fortune-100 customers like Morgan Stanley and Open Table - Founder-Market Fit: Our CEO previously founded Stormpath (acquired by Okta), where he created the first Authentication API for developers. He's done this before - and this time the market is 10x bigger. Our CTO led the vector database team at Redis, shipped 100+ LLM applications, and is a contributor to LangChain and LlamaIndex. He knows this space better than anyone. - Dream Team: We've assembled authentication, integrations, distributed systems, and AI experts from Okta, Redis, Microsoft, Splunk, Ngrok, Google, Airbyte, Disney, and HPE who've built and founded multiple successful developer platforms. - Perfect Timing: Every enterprise is racing to put agents in production - almost none get there. The problem isn't better models, it's proving which agent can take which action, on behalf of which user, against which system. That's us. - Massive Market : We're building critical infrastructure for the biggest technological shift of our generation. Every AI app will need what we're building. - Backed By The Best: Our Series A round is led by SYN Ventures, with strategic investment from Morgan Stanley and Wipro. Our earlier investors have also backed Databricks, Clickhouse, MongoDB, Perplexity, Cohere, ScaleAI, Confluent, Elastic, and Firebase. They see what we see - this is going to be huge. The Challenge Product Design's charter at Arcade is simple and hard: every surface where customers meet Arcade is a trust surface. For most of our customers — the AI/ML architects deploying Arcade inside their companies — the Dashboard is the only place they see us today, which is why it's where you start. Every fear they have about giving agents access to real systems either gets settled or amplified here. The work of design is to make sure it's the former. This is a new design space. Agents are non-deterministic. Tools fire in patterns customers didn't predict. Auth scopes nest in ways that aren't obvious. The Dashboard has to make all of that legible — for an admin granting an agent permission, an engineer debugging a failed tool call at 11pm, a compliance reviewer asking "what did the agent actually do?" Three different mental models, one product surface. There is no playbook for this. Nobody has shipped a definitive answer for how to design an admin UI for agents — the conventions we adopt will likely become the ones other companies copy. Some of your work is design. Some is teaching, explaining concepts customers haven't fully internalized yet, inside the product itself. If you'd rather inherit a design language than help invent one, this isn't the right role. And you're not just designing — you're building a function. There's no design team yet. There's no design language you inherit (engineering has stood up Radix and Tailwind patterns, but those are a starting point, not a system). You'll define how design works with engineering, how it works with the PM, and how it shows up in Marketing. Every pattern you set becomes the one the next designer inherits. This role reports to the Engineering Manager for Tools and Growth. The team is small, and you'll work across the entire company — shoulder-to-shoulder with engineering on the Dashboard, with the PM on Tools and Growth on what surfaces matter most, and with Marketing on how design decisions show up beyond the product. Your decisions land in customers' hands within weeks, not quarters. If you want to do the design work nobody has done yet — and watch customers learn from it — this is the role. What You'll Do - Own the design of major Dashboard surfaces end-to-end — flow, interaction, visual — from first sketch to shipped pixels. - Run customer research with the AI/ML architects deploying Arcade. Interview them. Watch them use prototypes. Bring the signal back to the team. - Pair daily with engineering. Hand off in Figma, watch implementation in our React + Tailwind codebase, and iterate when production reveals something the mock didn't. - Shape the design system alongside engineering. We use Radix and Tailwind today; what we ship next either reuses, extends, or replaces those patterns deliberately. - Make agent state legible — tool execution, auth scopes, observability, billing. All of it has to feel obvious in the moment a customer needs the answer. - Write the design rationale. Explain decisions so engineers, the PM, and Marketing can build on them — and so customers learn the model from the product itself.