Who We Are & What We’re Building

Eigen Labs is a frontier lab building coordination technologies for the post-AGI world. AGI is completely reconfiguring power, and a few major labs are already consolidating this power. We believe that coordination through open networks is the only counterforce that lets individuals maximize their agency.

We are building open networks for many different layers shaping AI: agentic research, inference infrastructure, and capital formation. Recently, we showed how a community of scientists, amateurs, and agents can collaborate to surpass Google’s unpublished quantum breakthrough, showcasing the power of open coordination.

What This Looks Like In Practice

A small number of companies are rapidly becoming gatekeepers to the most powerful systems ever created, trained on open internet, open research, and open-source software, now locked behind permission structures and centralized control.

The question isn't whether AI will transform society. The question is who gets to participate.

We believe:

Scientific discovery should remain open.
Intelligence should not be controlled by a handful of institutions.
Individuals should be able to coordinate, build, and create without asking for permission.
AI should empower people, not make them dependent.
AI should expand individual agency, not concentrate power.

This isn't a theoretical exercise. Darkbloom is already building distributed AI infrastructure from idle hardware around the world.

These are early examples of a much larger idea: open networks competing with centralized institutions.

We're looking for researchers, engineers, founders, scientists, designers, and builders who see the same trend we do and want to help build the alternative. If you're excited by open science, individual agency, coordination systems, and agentic infrastructure, we should talk.

Help us build what comes next. Learn more about working at Eigen here.

The Role

As a Senior Agentic AI Engineer at Eigen, You’ll work on the core systems that make AI agents actually usable in production. You’ve built real things - distributed systems, APIs, developer tools - and you’ve gone deep on agents, LLM pipelines, or autonomous workflows. You’re not just using AI tools - you have opinions on where this is going.

You will own large parts of the system and move quickly from idea → working product. You will spend most of your time building. Not managing. Not talking about roadmaps. Building.

This is a full-time role, remote-friendly, with a preference for U.S. time zones and close collaboration with the Seattle-based team.

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

What You’ll Bring

We care more about evidence than years of experience. Show us you’ve built hard things that work.

Strong signals we look for:

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 we look for:

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 when needed

Nice To Have

Experience with agent frameworks (LangChain, AutoGen, CrewAI, or custom systems)
Experience building multi-agent or orchestration systems
Familiarity with LLM evaluation, prompting, or performance tuning
Experience with workflow engines (Temporal, Airflow, Dagster)
Experience building developer platforms, SDKs, or internal tools
Exposure to retrieval systems, vector databases, or memory architectures
Interest in crypto, distributed systems, or verifiable compute

The target salary range for this role is $187,000 - $253,000. This is determined by a few factors including your skillset, prior relevant experience, quality of interviews and market factors at the point in time of offer. Other rewards may include short- and long-term incentives, and program-specific awards. In addition, Eigen Labs provides various employee benefits, including:

US Benefits

Competitive salary and non-cash compensation (tokens and equity)
World class benefits package (medical/dental/vision)
Remote work set up stipend
Flexible hours and a supportive remote environment
Flexible time off
401(k) retirement plan + company match
Monthly wellness benefit
Yearly off-sites
Paid parental leave

If hired outside of the US through an EOR, benefits will be offered based on specific country requirements and EOR offerings.

Equal Opportunity Employment

There's one more, very important thing. We are an equal opportunity employer. We search for amazing people of diverse backgrounds, experiences, abilities, and perspectives. We take care of each other to create an inclusive work environment where we love to come to work every day. We hope you can join us.

Remote AI & Machine Learning Jobs at Eigen Labs

Remote AI & Machine Learning Jobs at Eigen Labs