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Distributed Systems Engineer

Arcadeai
CompanyArcadeai
CategoryEngineering
LocationSan Francisco, California
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted13 May 2026
Last verified31 Jul 2026
SourceEmployer career page (ashby)
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Description
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. 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 We are building the runtime and registry for AI/LLM tools.  You will define both how AI interacts with the world, and how humans build and manage those tools. This includes creating production-grade integrations, and the services & toolkits that run them... and the solving the unique problems of AI/LLM usage along the way.  We are building a SaaS application first, and then allowing folks to run part of that infrastructure on-site via hybrid deployments.  This role is primarily focused on our back-end services, but as an early member of a startup, you’ll be working up-and-down the stack.  We build our software with Go, Python, and Typescript, and expect you to be a pro in at least one of those. We are looking for people who constantly ship and don't get stuck - we are looking for folks who are always learning and and able to apply that knowledge to their work and teach it to the team.   What You'll Do - Build the infrastructure to manage the backplane for all future AI tools - Design, build, test, and deploy high-performance, secure, production-grade software. - Develop SDKs and frameworks that make it easy for other developers to build custom tools - Help set industry standards for tool calling and authorization (for example, we helped write the MCP authorization spec) - Create integrations with major platforms and LLMs (Google Workspace, Microsoft 365, OpenAi, Anthropic, e
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Distributed Systems Engineer — Arcadeai · Job Opportunities API