Solo UnicornLab
Careers · Engineering & research

Member of Technical Staff.

Help a single founder do the work of an organization.

Apply by email Read our research

The opportunity

Build the whole loop.

Solo Unicorn Lab researches AI-native organizations: people and agents working together to discover problems, deliver products, and learn from users.

We are looking for a hands-on builder who can move between research and engineering. The work goes beyond generating code. It includes choosing the right problem, making agents work together, shipping something useful, and evaluating what actually improved.

Our published work is at an early stage. This role helps turn the research agenda into systems and experiments we can learn from.

What you will work on

From question to working system.

  • Agent systems that do useful work.

    Build workflows with tools, memory, shared context, and clear boundaries for human decisions.

  • Collaboration you can inspect.

    Design task handoffs, coordination, tracing and recovery so people and agents can work together reliably.

  • Products that learn from users.

    Connect problem discovery, prototyping, distribution, feedback and the next release.

  • Evidence of improvement.

    Create evaluations, compare against baselines, investigate failures, and document what changed.

What you bring

Strong engineering. Independent thought.

  • You can ship and operate software.

    Strong Python or TypeScript, experience with APIs and data systems, and the judgment to test, debug and maintain what you build.

  • You have built with language models.

    Hands-on experience with agent workflows, tool use, retrieval or memory, and evaluation. You know where these systems fail.

  • You care about the actual problem.

    You can work from an ambiguous need, talk to users, make trade-offs, and take responsibility for outcomes.

  • You make your reasoning visible.

    Clear writing, thoughtful experiments, and a willingness to change your view when the evidence changes.

Also valuable. Multi-agent systems, open-source contributions, research implementations, developer tools, or a product you have taken from idea to real users.

lab / apply

Show us what you have built.

Send one or two projects you are proud of, your part in them, and what you learned. Add a short introduction, a GitHub, portfolio or research link, and a problem in AI-native organizations you would like to explore. A résumé is welcome.

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