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# Founding Software Engineer

- **Company:** Postaladdress
- **Location:** München, Germany
- **Experience:** Experienced
- **Salary:** €100,000.0 - €200,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Data Infrastructure, Software Debugging, Programming Tools, Distributed Systems, Firmware, Hardware Design, Software Systems, Systems Integration, Integration Frameworks, Machine Learning Operations, Asynchronous Programming
- **Published:** September 25, 2026
- **Apply:** https://startup.jobs/founding-software-engineer-clera-10188355

## About the Role

* 3 or more years building complex, production-grade software systems end-to-end.
 * Strong proficiency in Rust or TypeScript.
 * Deep understanding of distributed systems, APIs, networking, and asynchronous programming.
 * Demonstrated experience building orchestration or scheduling systems that coordinate multiple concurrent processes or devices.
 * Experience building data infrastructure systems that capture state, events, and provenance at scale.
 * Experience building developer tooling, SDKs, or APIs for integration workflows.
 * Comfortable debugging and integrating across hardware, firmware, and software layers in production.
 * High agency and ownership in ambiguous, early-stage environments.
 * Experience with robotics, hardware integration, lab automation, embedded systems, or ML infrastructure is a strong plus.
 * No biology experience required.

## Description

This is a founding engineering role at an early-stage AI infrastructure company building software that connects AI agents to real-world laboratory systems. You will own critical infrastructure spanning experiment orchestration, agent connectivity, and distributed coordination, working at the intersection of software, robotics, and physical systems. Joining at the earliest stage, you will help define and build an entirely new product category., * Build experiment orchestration systems that schedule and coordinate experiments across distributed labs.

 * Connect AI agents to real-world instruments and experiments through robust agent infrastructure.
 * Design and implement data infrastructure to capture state, actions, measurements, failures, and provenance.
 * Architect distributed systems that reliably coordinate software, devices, and experiments at scale.
 * Develop developer tooling and APIs to accelerate new workflows and integrations.
 * Debug and optimize across the full stack, from software to hardware to physical systems.


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