Agentic AI Engineer

About this role

Eigen Labs is building the coordination engine for a world run by humans and AI agents alike.

We’re at an inflection point.

AI agents are no longer just tools - they’re becoming economic actors. They can write code, coordinate work, generate revenue, and increasingly operate with autonomy.

The problem is, none of this works in production today.

There’s no reliable way to verify what an agent actually did, what data it used, or who should get paid. The moment agents touch anything high-stakes - money, coordination, ownership—the system breaks.

What’s missing isn’t more intelligence. It’s trust.

## Tasks

What You Will Do

* Build agent runtimes and orchestration systems (planning, tool use, memory, coordination)
* Make agents reliable (retries, failure handling, state management)
* Make agents observable (tracing, debugging, evaluation)
* Make agents cheap (cost-aware execution, performance optimization)
* Make agents useful in production (not demos - real systems people depend on)
* Integrate LLMs, APIs, and external data into coherent, working systems
* Define how developers build, debug, and extend agent behavior

## Requirements

What You’ll Bring

We care more about evidence than years of experience.

Show us you’ve built hard things that work.

Strong Signals

* You’ve shipped real systems that people depend on
* You’ve taken ambiguous problems and turned them into working products
* You’ve built or deeply explored agent systems, LLM pipelines, or automation beyond simple demos
* You understand system behavior in production - failure modes, tradeoffs, reliability
* You move fast and iterate - you don’t wait for perfect specs

Technical Foundation

* Strong backend / systems experience (distributed systems, APIs, infrastructure)
* Proficiency in at least one core language (Python, Go, TypeScript, Rust, etc.)
* Experience with reliability patterns (state, retries, observability)
* Comfort working across the stack ...