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Salary: USD 186,000 - 242,000 / annual
Quo is an AI-powered communications platform for small businesses, bringing calls, texts, and customer information together in one easy-to-use system. Trusted by 120,000+ companies and rated #1 in customer satisfaction on G2, Quo is backed by Y Combinator, Tiger Global, and other top-tier investors.
The AI Agent Platform team owns the platform behind Quo's customer-facing AI agents, including Sona (for calls and texts) and Quo Agent (workspace agent). As a Staff Backend Engineer, you'll be the hands-on technical lead for this team, setting technical direction and writing significant portions of the code.
Key responsibilities:
- Own the architecture of the agent platform: how teams create and run agents, shared tool/integration pools, model call layers, and execution engines
- Build advanced orchestration for multi-agent coordination and long-running tasks
- Design memory and self-learning systems so agents improve from customer feedback
- Drive scale, performance, reliability, and cost efficiency as usage grows
- Make the platform accessible to other teams through documentation, defaults, and pairing
- Mentor engineers through design reviews, code reviews, and hands-on coaching
- Stay current with LLM and agent tooling developments and translate insights into roadmap proposals
Tech stack: Node.js and TypeScript backend, event-driven microservices (Temporal, RabbitMQ), Kubernetes on AWS, Postgres, MongoDB, Elasticsearch, Redis, Datadog observability, React/iOS/Android clients.
Quo is remote-first with intentional hub communities in select cities. The company values trust, autonomy, and action, with a culture focused on serving underserved small businesses.
REQUIREMENTS:
- Built and scaled backend of a product with real users; led architecture of business-critical services
- Shipped LLM-powered systems to production, ideally an agent platform or orchestration layer
- If no agent platform experience, must have built something similar (ML platform, workflow engine, real-time communications) with hands-on LLM depth
- Strong in TypeScript and Node, or fluent in another backend language (Go, Python, Java) with willingness to ramp up on Node
- High agency: self-directed, sees what needs doing and moves it forward
- Fast learner, plugged into AI world with knowledge of model/framework/tooling changes and opinions
- Writes clear design docs, explains trade-offs, brings teams along
- Customer-focused: weighs technical decisions against end-user experience
- Bonus: Temporal or durable workflow engine production experience; customer-facing AI product work; startup founder or early employee background
