Founding Engineer Rust (Full remote)

Stellenbeschreibung:

Our client is building the operating system for autonomous businesses. They build autonomous AI agents that run entire parts of a business. Not workflow automations, agents that learn, adapt, recover from errors, and make decisions. Built in Rust.

In just weeks of beta, over 100,000 AI agents have been deployed on their platform - automating trading systems, service businesses, workflows, and internal operations. Backed by a $10M seed round, they are redefining how companies run: AI agents connected to Slack, email, CRMs, payments, calendars, and beyond.

This is not incremental innovation. This is infrastructure for the next generation of digital companies. They are moving fast. Very fast.

Job Description

What we’re looking for

We’re hiring a founding engineer with entrepreneurial experience. You've built and shipped a product of your own as a founder, co-founder, or solo technical lead of an early‑stage venture. You carried it: architecture decisions, production debugging, shipping under pressure, wearing every hat. Whether it was acquired, wound down, or is behind you for other reasons, you came out of it with deep judgment and the drive to build again.

Profile / Requirements

What matters to us

Strong systems programming skills in Rust, Go, or C++, used regularly in your current or recent work
Production experience — you've built and operated systems used by real people, not just prototypes or demos
Active builder — you're currently shipping work we can look at (open-source contributions, personal projects, public repos)
End-to-end ownership mindset — you think about product outcomes and business impact, not just code
Comfort with ambiguity — you've made architectural decisions without a spec and lived with the consequences

Domains We Care About

AI agents, browser automation, LLM infrastructure, distributed systems, developer tooling. If you're building in one of these, we're especially interested.

What The Role Looks Like

You own systems end-to-end — architecture, implementation, production, and consequences. Small team, high intensity, minimal process. You define the approach rather than waiting for direction. Remote-friendly

How We Evaluate

No algorithmic puzzles. We assess four things:

Systems-level depth — real concurrency, async, memory and performance awareness
Shipped work — production systems used by real people
Autonomy under ambiguity — evidence of independent architectural judgment
Product ownership — you care about what the system does for users, not just how it's built